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Lessons From A Sensor Network Expedition
Abstract
Habitat monitoring is an important driving application for wireless sensor networks (WSNs). Although researchers anticipate some challenges arising in the real-world deployments of sensor networks, a number of problems can be discovered only through experience. This paper evaluates a sensor network system described in an earlier work and presents a set of experiences from a four month long deployment on a remote island o# the coast of Maine. We present an in-depth analysis of the environmental and node health data. The close integration of WSNs with their environment provides biological data at densities previous impossible; however, we show that the sensor data is also useful for predicting system operation and network failures. Based on over one million data and health readings, we analyze the node and network design and develop network reliability profiles and failure models.
... IoT devices are abnormally prone to diverse faults due to constraints such as minimal computational and energy resources, architectural problems, and disruptive environmental conditions [1], [2], [3], [4]. Faults can be caused by a complication in the device, such as loss of power or a bug in the software. ...
... For instance, devices in smart homes could experience faults on average two hours a day due to the power loss, network disruption, and hardware failure [1]. In other veins, experiments in exposed environments recorded half of the devices reporting incorrect states due to severe weather conditions [3]. Scope. ...
... Door is unlocked when user is not home (App8), SMS fails to send when there is movement on the patio (App6) and movement in the house when user is away (App9), window is closed at user-specified time (App11) App1,3,9 Motion sensor stuck at motion-inactive, AC stuck at on, heater fails to report its state ...
IoT devices are decentralized and deployed in un-stable environments, which causes them to be prone to various kinds of faults, such as device failure and network disruption. Yet, current IoT platforms require programmers to handle faults manually, a complex and error-prone task. In this paper, we present IoTRepair, a fault-handling system for IoT that (1)integrates a fault identification module to track faulty devices,(2) provides a library of fault-handling functions for effectively handling different fault types, (3) provides a fault handler on top of the library for autonomous IoT fault handling, with user and developer configuration as input. Through an evaluation in a simulated lab environment and with various fault injectio nmethods,IoTRepair is compared with current fault-handling solutions. The fault handler reduces the incorrect states on average 50.01%, which corresponds to less unsafe and insecure device states. Overall, through a systematic design of an IoT fault handler, we provide users flexibility and convenience in handling complex IoT fault handling, allowing safer IoT environments.
... telemetric data loggers. The miniaturization, low cost, ease of deployment, and auto-organization of wireless sensor networks has opened and widened the way of numerous elds of applications such as: target tracking [23] , disaster emergency response [18], ood detection [7], healthcare [24] , habitat monitoring and wildlife tracking [18], agriculture [5] [12]. The main purpose in this context is to provide a better understanding of the targeted environment and to support the decision making. ...
... telemetric data loggers. The miniaturization, low cost, ease of deployment, and auto-organization of wireless sensor networks has opened and widened the way of numerous elds of applications such as: target tracking [23] , disaster emergency response [18], ood detection [7], healthcare [24] , habitat monitoring and wildlife tracking [18], agriculture [5] [12]. The main purpose in this context is to provide a better understanding of the targeted environment and to support the decision making. ...
... In such a case, we will speak of a faulty measurement.. Moreover, the nature of the deployment environment [14] [8] and the characteristics of the WSN expose them to failures, due to incorrect packaging [18], battery depletion [21] [9], wrong calibration or software bugs [1]. The sensor can produce faulty measurements endangering the quality of the collected data. ...
Outlier detection is the process of identifying the data objects that do not comply with the normal behavior of the defined data model. Used in automated data analysis, it ensures the desired data quality and reliability. This field has attracted increasing attention in the wireless sensor network domain, using methods from machine learning, data mining, and statistics. In this paper, we propose a novel outlier detection approach based on Copula theory. This powerful theory allows to model the dependency between data measurements in a formal and statistical way. We have evaluated our proposed approach with a real world dataset. Our results show a detection rate of 85.90% and an error rate of 0.87%.
... Esta abordageḿ e pouco considerada em RSSF, pois os dispositivos são de baixo custo e possuem capacidades restritas, dificultando o uso de mecanismos para diagnóstico de um nó. Mecanismos indiretos de diagnóstico do nó, como a análise dos valores encontrados nos sensores, podem indicar futuras falhas [17]. ...
... Escolhemos esta plataforma devidoà sua grande aceitação na comunidade científica e ao elevado número de redes em operação que a utilizam. Simulamos uma aplicação com características de tráfego similaresà rede empregada na ilha de Great Duck para estudos do ecosistema e comportamento de aves [17]. Nesta rede, cada nó sensor envia mensagens de dados de 36 bytes a cada 70s. ...
Tolerância a falhas é um requisito essencial para o projeto de protocolos e aplicações para Redes de sensores sem fio (RSSF), pois falhas de hardware e comunicação são frequentes. Neste trabalho estudamos o comportamento de protocolos de roteamento para redes de disseminação contínua de dados perante a ocorrência de falhas. Apresentamos os principais agentes causadores de falhas silenciosas, incluindo ataques de segurança. Classificamos estas falhas quanto a extensão e persistência, e utilizamos esta classificação para avaliar, via simulação, protocolos de roteamento para redes de disseminação contínua de dados. Verificamos que falhas em grandes regiões da rede são o tipo mais prejudicial, e mostramos como protocolos de roteamento podem economizar energia desligando temporariamente nós isolados da rede.
... Lorincz et al., 2004), or a generic function, such as habitat monitoring (e.g. Szewczyk et al., 2004). Akyildiz et al. (2002), Chong and Kumar (2003), and provide further details on the history and development of ESNs. ...
... A series of projects where ESNs have been developed in this way have been reported globally. These include Berkeley's modelling of bird populations at Great Duck Island (Szewczyk et al., 2004); the NASA/JPL project on biological flourishes and hydrology in Antarctica (Delin et al., 2003 and2004", respectively); ...
p>The mechanisms that control glacier dynamics and fast ice stream flow are still poorly understood, largely due to the inaccessibility of the subglacial environment. One of the ways to improve on current investigations is to broaden the methods used to monitor the subglacial environment. An autonomous multi-sensor wireless probe was developed for use within an Environmental Sensor Network at Briksdalsbreen, Norway. Probes were deployed at the base of boreholes, measuring temperature, pressure, resistance (a proxy for conductivity), case strain, and tilt, six times a day. The probes used radio communications to transfer data to a base station at the glacier surface. The data was then sent to a reference station, which uploaded it onto the internet on a daily basis. In excess of a year's worth of data was obtained from several probes, deployed between 2004-2006. Readings of case strain and tilt indicated when the probes had become incorporated into the deforming bed. A reduction in sensor activity was displayed as the glacier changed from a summer to a winter regime. In the following spring, the sensors showed an increase in activity, particularly in water pressure. An Emergent Spring Event was recorded in February, followed by the actual Spring Event. This marked a transition to summer conditions within the glacier's hydrological system. Sliding was the dominant mechanism of basal motion during this time. In the summer, the probes began to rotate as the dominant form of basal motion transferred from sliding to till deformation. The movement of the probes was in keeping with the Taylor (1923) mechanism of clast rotation. Sedimentological analyses under the scanning electron microscope presented a relatively simple model for grain erosion within the deforming bed. Erosion occurs within a continuum whereby processes of both fracture and abrasion combine, generating intermediate grain forms. The style of deformation experienced is controlled by the nature of the bedrock and the overall strain imposed on the till. At Briksdalsbreen there was good evidence for erosion, but little evidence for the production of a significant silt component. This investigation demonstrates the potential for the use of ESNs within glacial environments. The probes provide a successful means by which the properties of and processes operating within the subglacial environment can be assessed over broad temporal and spatial scales. For the first time, activity was recorded within the subglacial environment much earlier than previously expected (January) and the spring event within unconnected regions of the bed was monitored and characterised. The records produced highlighted the complexity of hydro-mechanical interactions and the need for further study to constrain these processes. The probes also provided the first natural records of in situ clast rotation from within the deforming bed. This movement may have implications for models of clast rotation, the identification and classification of sediments, and models of grain interactions on the micro-scale.</p
... Furthermore, the sink and the links between the sink and nodes can experience failures. For example, in deployments [2]- [5], the sinks were not accessible over time due to different reasons. In [2], 4 of the 7 nodes had communication failure with the sink over time, furthermore, the authors observed a sink outage due to power failure. ...
... Likewise, in [4], two weeks of data were lost due to a sink outage. In [5], the sink went down due to harsh weather. ...
... Battery failure is a major cause for faulty data (Szewczyk et al., 2004). Depletion of the batteries leads to transmission of faulty data by the sensors. ...
... As WSNs are deployed in harsh conditions hardware errors are quite frequent. One such instance of hardware fault is when the hardware short circuits due to the presence of water content (Szewczyk et al., 2004). Other techniques that discuss detection of hardware faults can be found in Tei (2013), Lau et al. (2014), Mo et al. (2015), Jin et al. (2015), Banerjee et al. (2011), Panda and Khilar (2014), Yuvaraja and Sabrigiriraj (2015), Kaur and Sharma (2010), Kamal et al. (2014), Yang et al. (2014), and Nguyen et al. (2013). ...
Wireless sensor networks have emerged as a key technology which is used in many safety critical applications. The sensors in wireless sensor network have to be deployed in hostile, harsh and unattended environments for long periods of time. This creates a great challenge in providing a good quality of service. This results in introductions of faults, sensor failures, communication failures and changes in topology. Hence, efficient fault detection techniques are required for good quality of service. In this article, we survey various fault detection techniques and provide a new taxonomy to integrate new fault detection techniques. We perform a qualitative comparison of the latest fault detection algorithms. From a qualitative analysis, we select a list of techniques that are analyzed quantitatively. We also discuss the shortcomings, advantages and future research directions for fault detection in wireless sensor networks.
... There is remote sensing in the mi-controller with limited memory and limited battery supplies. Water quality, healthcare, military, wildlife pollution, and industrial monitoring are some WSN applications [11,12,13]. Below, briefly, are mentioned some applications of WSN. ...
Wireless Sensor Networks (WSN) are widely used in many applications. However, it still suffering from many issues such as packet loss, idle listening, high delay,
and distance between nodes which all contribute to increase energy consumption and dissipation in WSN. In order to reduce this energy dissipation, this research concentrates on the Hierarchal routing Medium Access Control (MAC) protocols
on how to solve the aforementioned problems. This research proposes the Grid
Mediation Device (GMD) Node to minimize the idle listening of the active duration for each node, the nodes are put to sleep mode for a reasonably long period
of time and they wake up for a short time only to receive data. This behavior
reduces the energy consumption for each sensor while minimizing the delay since
the clusterheads will not wait for the sleeping nodes that have no data to send.
Thereafter, the active clusterheads will be also put in the sleeping mode once they
finish their data transmission. Simulation and mathematical model of the proposed
GMD protocol have confirmed that the proposed GMD can improve the lifetime for all sensor nodes in the network, due to minimizing the idle listening time for
each node. Moreover, adding Multi-levels of grids and Multi-level of MD node to the GMD protocol that will minimize the distance of sending data from each level
cluster grid to another level until reach to the base station instead of sending data
directly from any cluster to the base station, because the path between nodes and
cluster head is not reliable and the nodes are far from each other in different grid. This research leads to reduce packets lost problem as well makes the network more reliable which is another contribution of this study. Lastly, this research adding Fuzzy logic system to the grids to minimize the problem of the distance between
nodes as using three fuzzy logic criteria for each node will lead to choosing the
optimal location and energy for each clusterhead and each node. The three proposed protocols have been compared to the Two-Dimensional Technique Based on
Centre of Gravity and Energy (TDTCGE) protocol which is used two-dimensional technical centers (energy Centres and Gravity Centres) that will help to reduce the energy consumption and distances between nodes. Moreover, some of the proposed
protocol derives better system performance such as end-to-end delay, throughput, lifetime, and energy saving. The Grid Mediation Device (GMD) protocol with
Mathematical model has improved the lifetime around 88% as compared with the
TDTCGE. In addition, The Fuzzy Logic grids (FLG) protocol saves more than
8% energy battery by adding the Fuzzy logic with the three criteria’s (Distance between nodes, distance to the basestation, residual energy) that will minimize theradius competitions between nodes and the clusterhead, and between the nodes and BS by 52% more than TDTCGE protocol. GMD Simulation protocol decreases the mean of delay by 40% because of the sleeping mode, and which node
has data that it has the turn to transmit data only. In addition, Multilevel GMD Proposed protocol reduces the packets lost by 65%. This Research Work improves the lifetime and saving more energy which is also more reliable and efficiency for the wireless sensor network
... The hardware issues such as network connectivity and malfunction in an internal component of the sensor may be cause of the failure sensor network. By Szewczyk et al. [26,27], when temperature and humidity sensor is placed in the water, then it gives unexpected sensor measurements due to a short circuit of the power terminals. Similarly, when soil contact with electrode sensor leads to failure network due to high radiation and weather conditions [28,29]. ...
This paper covers the basics of fault diagnosis in wireless sensor networks, as well as fault diagnosis terminology, sensor fault classification, causes and effects, and fault diagnosis performance metrics. In recent years, it has been observed that a large variety of fault diagnosis techniques have been proposed by researchers. The existing fault diagnosis methods for sensor networks can be divided into three categories: centralised, distributed, and hybrid approach. This paper gives a detailed review of state-of-the-art wireless sensor network fault diagnosis approaches. It specifically discusses some existing automated fault detection and diagnosis approaches in wireless sensor networks, as well as their benefits and drawbacks.
... e author in [15] pointed out that annexing ambient energy is not the only necessary process in energy harvesting, but energy storage is also critical. e untimely depletion battery adversely affects remote nodes, even at practical installations [16]. us, a supercapacitor, which has a longer lifecycle and is more efficient than a battery, should be considered when implementing a solar energy harvesting system at remote nodes. ...
Recent surveys in the energy harvesting system for seismic nodes show that, most often, a single energy source energizes the seismic system and fails most frequently. The major concern is the limited lifecycle of battery and high routine cost. Simplicity and inexperience have caused intermittent undersizing or oversizing of the system. Optimizing solar cell constraints is required. The hybridization of the lead-acid battery and supercapacitor enables the stress on the battery to lessen and increases the lifetime. An artificial neural network model is implemented to resolve the rapid input variations across the photovoltaic module. The best performance was attained at the epoch of 117 and the mean square error of 1.1176e-6 with regression values of training, test, and validation at 0.99647, 0.99724, and 0.99534, respectively. The paper presents simulations of Nsukka seismic node as a case study and to deepen the understanding of the system. The significant contributions of the study are (1) identification of the considerations of the PV system at a typical remote seismic node through energy transducer and storage modelling, (2) optimal sizing of PV module and lead-acid battery, and, lastly, (3) hybridization of the energy storage systems (the battery and supercapacitor) to enable the energy harvesting system to maximize the available ambient irradiance. The results show the neural network model delivered efficient power with duty cycles across the converter and relatively less complexities, while the supercapacitor complemented the lead-acid battery and delivered an overall efficiency of about 75%.
... Apart from the above usages, most of the researchers are using Wireless Sensor Networks to the production of agriculture (12). For crop protection in fields the WSN were designed for the animal diversion intrusions in crop fields as this was the major threats to crop yield (13). Apart from pest control, various application of WSNS in agriculture areas like Soil-irrigation (14),land-fertilization (15), and greenhouse (16). Industrial Wireless Sensor Networks (IWSNs) can be classified into following three groups that are as under (18): In this century environment sensing became the widest group of Wireless Sensor Network application (19). ...
Wireless Sensor Networks (WSN) becomes a point of intrest in technologies that is being utilized in several modules. The WSN have been deployed in the unattended environment, hostile and harsh for a long interval of time. By doing the good quality of service, a great challenge has been created. That introduced the faults, communication failure and sensor failures or even in a change in topologies as well. This study focuses on the various faults that can cause the network failure or may become the reason for packet loss. Numerous reliability issues arise when packet loss situation occurs in the network. Moreover, it leads to the reduction of the network performance and decrement inefficiency of the network. To tackle such kinds of faults, one should apply different fault management techniques so as to ensure reliability and increase performance as well as reliability. In this study, we reviewed several aspects related to the fault management of WSN.
... Usually, after an update, nodes reboot, so data and state are reset. Moreover, IoT networks are susceptible to changes of the environmental conditions [43] that can result to temporary node disconnections. ...
The Internet-of-Things (IoT) presents itself as an emerging technology, which is able to interconnect a massive number of heterogeneous smart devices for supporting complex data-driven applications in a variety of domains, such as smart-cities, healthcare, industrial automation etc. Throughout their extended lifetime, the devices forming the IoT networks need to be re-programmed over-the-air, so that new features are added, software bugs or security vulnerabilities are resolved and their applications can be re-purposed. The limitations of IoT devices, such as installation in locations with limited physical access, resource-constraint nature, large scale and high heterogeneity, should be taken into consideration for designing an efficient and reliable pipeline for over-the-air programming (OTAP). In this work, we present an overview of OTAP techniques that can be applied to IoT networks. We highlight the main challenges and limitations of OTAP for IoT devices and analyse the essential steps of firmware update process, along with different approaches and techniques that implement them. In addition, we discuss schemes that focus on securing the OTAP process. Finally, we present a collection of state-of-the art open-source and commercial platforms that integrate secure and reliable OTAP.
... However, they are prone to faults caused by factors such as power outages [1] and network disruption [2]; frequency of faults is also increased due to IoT device design constraints such as low computation capacity [3] and small batteries [4]. Additionally, devices face complex issues, such as disruptive environmental conditions like weather and collisions [5], user error during deployment in environment [1], and flaws in the device hardware and software [6]. A study shows that devices in smart homes can experience faults more than 4 hours a day due to power loss, network disruption, and hardware failure [4], and a more recent work shows that a temperature sensor experiences more than 15% faulty temperature readings [2]. ...
... Jeffery et al. [61] present a framework, called Extensible Sensor stream Processing (ESP), to clean the both time and space correlated sensor data in the pervasive applications. Apart from the space and time correlated failure, Szewczyk et al. [111] find that failure of temperature sensors is highly correlated with the failure of the humidity sensors in their lessons from a sensor network expedition. Researchers from data mining community also provide valuable analytic models for such co-related sensor data. ...
The field of IoT has blossomed and is positively influencing many application domains. In this paper, we bring out the unique challenges this field poses to research in computer systems and networking. The unique challenges arise from the unique characteristics of IoT systems such as the diversity of application domains where they are used and the increasingly demanding protocols they are being called upon to run (such as, video and LIDAR processing) on constrained resources (on-node and network). We show how these open challenges can benefit from foundations laid in other areas, such as, 5G cellular protocols, ML model reduction, and device-edge-cloud offloading. We then discuss the unique challenges for reliability, security, and privacy posed by IoT systems due to their salient characteristics which include heterogeneity of devices and protocols, dependence on the physical environment, and the close coupling with humans. We again show how the open research challenges benefit from reliability, security, and privacy advancements in other areas. We conclude by providing a vision for a desirable end state for IoT systems.
... Specifically, WSNs are prone to failures when nodes are deployed in harsh environments. Atmospheric phenomena, such as changes in weather modify signal propagation, which may in turn cause communication errors as signal strength decreases [19]. Several environmental conditions such as humidity and temperature can modify signal propagation. ...
Through the use of UAV, the functional lifetime of WSN can be elongated in exchange for higher data delivery latency as the UAV replaces the multi-hop communication among nodes during data acquisition. Due to the NP-hardness of the TSP whose computational complexity increases exponentially as an increment of number of nodes, heuristic algorithms, such as nearest neighbor heuristic TSP algorithm (NN), have been developed for reducing this data delivery latency in shortest possible time. In our previous research work we have published the directional NN algorithm directed to the next nearest node (DDNN) (Alemayehu and Kim in Wirel Pers Commun 95:3271–3285, 2017) which modifies the existing NN algorithm to gain a reduction in this data delivery latency. However, the DDNN algorithm does not consider the reliability of the system in case of node or link failures. To collect the sensing data rapidly and reliably, the DDNN algorithm should be able to react to node or link failures and manage the data transmissions effectively in the network. In this study, we propose an extension of the DDNN scheme, fault tolerable DDNN scheme for data gathering to gain a reduction in the data acquisition time with fault-tolerant capability. The performance analysis has demonstrated that our proposed algorithm tolerates fault in case of malfunctions of sensors due to node/link failures and improves the detection rate of the DDNN scheme up to 34.93% at the cost of a little bit distance.
... By adjusting its measurement tasks, data processing and network communication frequency, it can adapt to a variety of work environment, and make the ocean researchers to get more space distributed data. In 2002, University of Pennsylvania in the United States designed a wireless sensor network system monitoring lake or reservoir PH indicators [3]. Each node contains the environment sensor and plays the role of data routing and use sound waves to achieve the communication between the underwater nodes. ...
The wetland that known as "the kidney of the earth" is an ecological system with many resources. Monitoring of wetland environment includes the monitoring of water quality, air and soil. The parameters of temperature, pH value, turbidity, dissolved oxygen (DO), water level, conductivity of water, illuminance, PM2.5, harmful gas, and soil moisture is particularly important for the survival of animals in wetland. Real-time monitoring wetland environment is conducive to understanding the causes and trends of environmental change in the whole region, so as to make environmental change emergency strategies timely. The author introduces a real-time monitoring system based on Multi-sensor Combination Module (MSCM) and LoRa. This system has two types of MSCM, one is for water and the other is for air. The MSCM for water consists of six sensors, such as water temperature sensor, pH sensor, turbidity sensor, dissolved oxygen sensor, conductivity sensor, and water level sensor, and stm32 core processor, which has the advantages of low power consumption and high speed. The data collection node uploads the collected data to the base station through a LoRa module with low power consumption, high speed and wide coverage. The base station and the collection node are connected in a star. The LoRaWan protocol is used to realize the communication between acquisition nodes and sink. In the case of code rate is 4/5, bandwidth is 500 kHz and spreading factor is 12, the effective throughput of the system can reach 1172 bps. At the same time, a data fusion algorithm based on fuzzy decision is designed for data processing on the acquisition nodes to reduce the amount of uploaded data, reduce power consumption and improve network throughput. Experiments show that the system has strong stability, flexible networking, low power consumption, long communication distance, and is suitable for wetland environmental monitoring.
... Apart from the above usages, most of the researchers are using Wireless Sensor Networks to the production of agriculture (12). For crop protection in fields the WSN were designed for the animal diversion intrusions in crop fields as this was the major threats to crop yield (13). Apart from pest control, various application of WSNS in agriculture areas like Soil-irrigation (14),land-fertilization (15), and greenhouse (16). Industrial Wireless Sensor Networks (IWSNs) can be classified into following three groups that are as under (18): In this century environment sensing became the widest group of Wireless Sensor Network application (19). ...
... Unlike Wi-Fi/LTE, LoWPANs do not use physical-layer techniques like adaptive modulation/coding or multi-antenna beamforming. Thus, they are directly impacted by link quality degradation due to varying environmental conditions [112,127]. Additionally, IEEE 802.15.4 coexists with Wi-Fi in the 2.4 GHz frequency band, making Wi-Fi interference particularly relevant in indoor settings [99]. As LoWPANs are embedded networks, there is no human in the loop to react to and repair bad link quality. ...
Low-power and lossy networks (LLNs) enable diverse applications integrating many resource-constrained embedded devices , often requiring interconnectivity with existing TCP/IP networks as part of the Internet of Things. But TCP has received little attention in LLNs due to concerns about its overhead and performance, leading to LLN-specific protocols that require specialized gateways for interoperability. We present a systematic study of a well-designed TCP stack in IEEE 802.15.4-based LLNs, based on the TCP protocol logic in FreeBSD. Through careful implementation and extensive experiments , we show that modern low-power sensor platforms are capable of running full-scale TCP and that TCP, counter to common belief, performs well despite the lossy nature of LLNs. By carefully studying the interaction between the transport and link layers, we identify subtle but important modifications to both, achieving TCP goodput within 25% of an upper bound (5-40x higher than prior results) and low-power operation commensurate to CoAP in a practical LLN application scenario. This suggests that a TCP-based transport layer, seamlessly interoperable with existing TCP/IP networks, is viable and performant in LLNs.
... A 43-node sensor deployment on the uninhabited Great Duck Island was one of the first emphasizing the unattended operation of sensor systems. A key lesson was the necessity of rigorous testings as the deployment scaled from a lab environment to the field [22,26]. The development of an easily accessible testbed described in Section 5.3 allowed us to identify a large number of errors pre-deployment and contributed strongly to our low in-field failure rate. ...
The vision of sensor systems that collect critical and previously ungathered information about the world is often only realized when sensors, students, and subjects move outside the academic laboratory. However, deployments at even the smallest scales introduce complexities and risks that can be difficult for a research team to anticipate. Over the past year, our interdisciplinary team of engineers and economists has been designing, deploying, and operating a large sensor network in Accra, Ghana that measures power outages and quality at households and firms. This network consists of 457 custom sensors, over 3,000 mobile app instances, thousands of participant surveys, and custom user incentive and deployment management systems. In part, this deployment supports an evaluation of the impacts of investments in the grid on reliability and the subsequent effects of improvements in reliability on socioeconomic well-being. We report our experiences as we move from performing small pilot deployments to our current scale, attempting to identify the pain points at each stage of the deployment. Finally, we extract high-level observations and lessons learned from our deployment activities, which we wish we had originally known when forecasting budgets, human resources, and project timelines. These insights will be critical as we look toward scaling our deployment to the entire city of Accra and beyond, and we hope that they will encourage and support other researchers looking to measure highly granular information about our world's critical systems.
... In this paper, we propose an improved protocol, called the BranChain, short for the branched chain routing protocol, on the basis of the routing paths generated by chain-based protocol and the analysis of PEGASIS protocol. We consider a situation in which the network collects information periodically from a flat terrain where each node continually senses the environment and sends the collected data (including the readings of the light, humidity and temperature) back to the BS (Szewczyk et al., 2004). ...
In order to solve the deficiencies with the PEGASIS in the inevitability of long link, the overhead of the ineligible cluster head (CH), and the overhead and time cost of chain rebuilding, an improved protocol, the BranChain, is proposed. The proposed algorithm can avoid long links, re-adjust network topology and adopt CH re-election mechanism. Whenever a long link is formed, the node originally connected is supposed to form a new independent branched chain with the greedy algorithm. When all nodes get connected in the chain, the system will connect all the independent branched chains together by searching for the optimal paths between each two of the branched chains. When the sensor nodes die, the two broken branched chains will be connected with the same algorithm as that of the optimal paths searching. Simulation results show that the BranChain, compared with the PEGASIS, can significantly prolong the network lifetime.
... Static environmental WSNs have been established to monitor moisture, temperature, precipitation, solar radiation and wind speed (e.g. Szewczyk et al. 2004;Barrenetxea et al. 2008). To date, wildlife sensing WSNs have utilised microphone arrays and acoustic sensors (e.g. ...
Context: Wireless sensor networks (WSNs) are revolutionising areas of animal behaviour research and are advantageous based on their ability to be deployed remotely and unobtrusively, for long time periods in inaccessible areas. Aims: We aimed to determine the feasibility of using a WSN to track detailed movement paths of small animals, e.g. rats (Rattus spp.) 100-400 g, too small for current GPS technology, by calibrating active Radio Frequency Identification (RFID) tags and loggers using Radio Frequency Signal Strength Indicator (RSSI) as a proxy for distance. Active RFIDs are also called Wireless Identification (WID) tags. Methods: Calibration tests were conducted using a grid of loggers (n = 16) spaced at 45-m intervals in clear line-of-sight conditions. WID tags (n = 16) were placed between the loggers at 45-m intervals. Eight 'walks' were also conducted through the grid using a single WID tag. This involved attaching the tag to a small bottle of water (to simulate the body of an animal), towed around the grid using a 1-m long tow line attached to a volunteer walker. The volunteer also held a GPS device that logged their track. Models were constructed to test the effects of distance, tag movement and individual differences in loggers and tags on the reliability of movement data. Key results: Loggers were most successful at detecting tags at distances <50 m. However, there was a significant difference in the detection probabilities of individual loggers and also the transmission performance of individual tags. Static tags were less likely to be detected than the mobile tag and although RSSI was somewhat related to distance, the reliability of this parameter was highly variable. Implications: We recommend caution in the future use of current radio frequency ID tags in wireless sensor networks to track the movement of small animals, and in the use of RSSI as an indicator of individual distance values, as extensive in situ calibration is required. 'Off the shelf' devices may vary in performance, rendering data unreliable. We emphasise the importance of calibrating all equipment in animal tracking studies to reduce data uncertainty and error.
... The data should be authentic which means when the packet is received, it should be verified that it comes from a trusted source. If authentication is not there, the attackers can tamper the message anywhere in between due to which wrong message would be transmitted to the sink [5]. ...
... stuck readings, M.M. Rajabi et al. Journal of Hydrology 567 (2018) 457-477 out of range errors, abrupt shifts, abnormal noise, etc., see Szewczyk et al., 2004), and hence requires the integration of fault detection methods in groundwater MDI techniques especially when sensor readings are fed automatically into models. An example of studies addressing this issue is Barnhart et al. (2010), which employs a data reduction algorithm to identify and remove potentially faulty salinity data, and then uses the remaining data for groundwater model parameter estimation by PEST. ...
We define model-data interaction (MDI) as a two way process between models and data, in which on one hand data can serve the modeling purpose by supporting model discrimination, parameter refinement, uncertainty analysis, etc., and on the other hand models provide a tool for data fusion, interpretation, interpolation, etc. MDI has many applications in the realm of groundwater and has been the topic of extensive research in the groundwater community for the past several decades. This has led to the development of a multitude of increasingly sophisticated methods. The progress of data acquisition technologies and the evolution of models are continuously changing the landscape of groundwater MDI, creating new challenges and opportunities that must be properly understood and addressed. This paper aims to review, analyze and classify research on MDI in groundwater applications, and discusses several related aspects including: (1) basic theoretical concepts and classification of methods, (2) sources of uncertainty and how they are commonly addressed, (3) specific characteristics of groundwater models and data that affect the choice of methods, (4) how models and data can interact to provide added value in groundwater applications, (5) software and codes for MDI, and (6) key issues that will likely form future research directions. The review shows that there are many tools and techniques for groundwater MDI, and this diversity is needed to support different MDI objectives, assumptions, model and data types and computational constraints. The study identifies eight categories of applications for MDI in the groundwater literature, and highlights the growing gap between MDI practices in the research community and those in consulting, industry and government.
... Taxonomy papers [1,6,10,21,[25][26][27] discuss an abstract notion of WSN failures, and create taxonomies of the causes of WSN failure. Lessons learned papers [2,7,11,16,18,19,22,30] document the failures encountered, and the lessons learned from actual WSN deployments in the wild (not in a lab or WSN testbed). We felt that there were not enough lessons learned papers which documented actual failures during WSN deployments. ...
This document presents the views expressed in the submissions and discussions at the FAILSAFE workshop about the common problems that plague embedded sensor system deployments in the wild. We present analysis gathered from the submissions and the panel session of the FAILSAFE 2017 workshop held at the SenSys 2017 conference. The FAILSAFE call for papers specifically asked for descriptions of wireless sensor network (WSN) deployments and their problems and failures. The submissions, the questions raised at the presentations, and the panel discussion give us a sufficient body of work to review, and draw conclusions regarding the effect that the environment has as the most common cause of embedded sensor system failures.
... Wireless Sensor Networks (WSNs) consist of spatially distributed, autonomous, wireless, networked sensing devices that can be used to monitor a physical space (Yick et al. 2008;Sharma et al. 2016). WSNs have gained increasing popularity for a range of applications, such as environmental monitoring (Khedo et al. 2010;Bhattacharya et al. 2012;Postolache et al. 2014;Adamo et al. 2015), animal tracking (Szewczyk et al. 2004;Pereira et al. 2008;Amundson and Koutsoukos 2009; ...
Wireless Sensor Networks (WSNs) are crucial in supporting continuous environmental monitoring, where sensor nodes are deployed and must remain operational to collect and transfer data from the environment to a base-station. However, sensor nodes have limited energy in their primary power storage unit, and this energy may be quickly drained if the sensor node remains operational over long periods of time. Therefore, the idea of harvesting ambient energy from the immediate surroundings of the deployed sensors, to recharge the batteries and to directly power the sensor nodes, has recently been proposed. The deployment of energy harvesting in environmental field systems eliminates the dependency of sensor nodes on battery power, drastically reducing the maintenance costs required to replace batteries. In this article, we review the state-of-the-art in energy-harvesting WSNs for environmental monitoring applications, including Animal Tracking, Air Quality Monitoring, Water Quality Monitoring, and Disaster Monitoring to improve the ecosystem and human life. In addition to presenting the technologies for harvesting energy from ambient sources and the protocols that can take advantage of the harvested energy, we present challenges that must be addressed to further advance energy-harvesting-based WSNs, along with some future work directions to address these challenges.
... In this paper, we propose an improved protocol, called the BranChain, short for the branched chain routing protocol, on the basis of the routing paths generated by chain-based protocol and the analysis of PEGASIS protocol. We consider a situation in which the network collects information periodically from a flat terrain where each node continually senses the environment and sends the collected data (including the readings of the light, humidity and temperature) back to the BS (Szewczyk et al., 2004). ...
... WSNs are deployed in particular environments including glaciers, forests, and mountains in order to gather environmental parameters during long periods. Temperature, moisture or light sensor readings allow analyzing environmental phenomena, such as the influence of climate change on rock fall in permafrost areas [14]. ...
The future Internet, designed as an ―Internet of Things‖ is foreseen to be ―a world-wide network of interconnected
objects uniquely addressable, based on standard communication protocols‖ [1]. Identified by a unique address, any
object including computers, sensors, RFID tags or mobile phones will be able to dynamically join the network,
collaborate and cooperate efficiently to achieve different tasks. . Including WSNs in such a scenario will open new
perspectives. Covering a wide application field, WSNs can play an important role by collecting surrounding context
and environment information.Key enablers for the IoT paradigm are : RFID and WSN. RFID is well known and
established for low-cost identification and tracking. WSNs bring IoT applications richer capabilities for both sensing
and actuation. In fact, WSN solutions already cover a very broad range of applications, and research and technology
advances continuously expand their application field.However, the sheer diversity of WSN applications makes
increasingly difficult to define ―typical‖ requirements for their use in IoT applications [2]. The generic WSN
platforms can be used with good results in a broad class of IoT environmental monitoring applications. However,
many IoT applications (e.g., those in open nature) may have stringent requirements, such as very low cost, large
number of nodes, long unattended service time, ease of deployment, low maintenance, which make these generic
WSN platforms less suited.
... To ensure environmental sustainability, it is critical to have effective monitoring systems. Environmental monitoring systems have been developed for monitoring air quality [Cordova-Lopez et al. 2007;Khedo et al. 2010;Bhattacharya et al. 2012], water quality [Sanders 1983;Chapman 1996;Farrell-Poe 2005;Strobl and Robillard 2008], animal tracking [Szewczyk et al. 2004;Pereira et al. 2008;Amundson This work was funded in part by the National Science Foundation under research grant CNS-1239423. Authors' addresses: K. S. Adu-Manu, C. Tapparello, and W. Heinzelman, Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY 14627; emails: kadumanu@ur.Rochester.edu, ...
Water is essential for human survival. Although approximately 71% of the world is covered in water, only 2.5% of this is fresh water; hence, fresh water is a valuable resource that must be carefully monitored and maintained. In developing countries, 80% of people are without access to potable water. Cholera is still reported in more than 50 countries. In Africa, 75% of the drinking water comes from underground sources, which makes water monitoring an issue of key concern, aswatermonitoring can be used to trackwater quality changes over time, identify existing or emerging problems, and design effective intervention programs to remedy water pollution. It is important to have detailed knowledge of potable water quality to enable proper treatment and also prevent contamination. In this article, we review methods for water quality monitoring (WQM) from traditional manual methods to more technologically advanced methods employing wireless sensor networks (WSNs) for in situ WQM. In particular, we highlight recent developments in the sensor devices, data acquisition procedures, communication and network architectures, and power management schemes to maintain a long-lived operational WQM system. Finally, we discuss open issues that need to be addressed to further advance automatic WQM using WSNs.
The past few years have witness growing interest in the prospect use of wireless sensor
networks (WSNs) in enormous domain of applications and it became an interesting
research area. WSNs are a type of network that consists on number of nodes that connect
with each other without a physical medium. The nodes are tiny size and consist on a small
battery with limited energy and unplugged with power resources. The sensor network
formally contain on two types of nodes: member nodes (MN), which has to detect action
from surrounding area and send the detecting signal to each other until it reach the source
node. As well as, the sink node (S), this has a task of collecting the sensing data from
member nodes. A main problem faces this type of network is that; the nodes which are
close to the sink will deplete their power faster than other nodes because the whole data
throughput path comes throw these nodes. Researcher tries hardly to solve this problem by
suggesting many protocols that help to disband this issue, beside many routing protocols
that been suggested to pass the data throw the network, many other protocols suggest that to divide the sensing area into grids or cells as clusters, each group of nodes connect with each other and send their detective data packet to one of cluster nodes which called cluster-head (CH). CHs task inside the network is to connect with each other in order to receive the data from MNs and send it to S. Many networks developers suggest that the sink has to be routable and moves around the network and collect data from MNs directly. The mobile sink can reduce the energy depletion of the nodes subsequently will enhance the network lifetime. The major issue while utilising this technique is how to detect the sink while moving. In our thesis, we initiate a similar network that been divided into multi-clusters and each cluster contain a cluster-head, and the sink has to be routable in order to ease the data collection process by reducing the number of hops for data packet from source to destination. We suggest a new protocol called Hexagonal Grid based Dynamic routes Adjustment (HGDRA) which divides the network cells into hexagonal cells and used the mobile sink technique inside the network area. Our technique is tries to reconstruct a data packet path that detect the mobile sink with less energy consumption, as well as, less number of hops. We gain a better result in aspects of network reconstruction cost, number of hops, nodes residual energy and network lifetime in general. As well as, we suggest a hybrid version of our first protocol with additional sink route reconstruction mechanism called Hexagonal Grid based Dynamic routes Adjustment with Smart sink (HGDRA-S). The new suggested technique with the smart sink helps to improve the data collection mechanism, furthermore, improved the network lifetime. We demonstrate our result via the same performance evaluation factors that we used in the first protocol. We used Ns2
simulator to demonstrate our result by comparing our suggested protocols with the base work protocol and we gain a significant improvement for both protocols.
WSNs are infiltrating the environment in its wide sense, indoors and outdoors, in the human body, in unapproachable emplacements; they have found their way into a wide variety of applications and systems with vastly varying requirements and characteristics. Guardian angels? Watchdogs? Whatever, they are intended to work properly, faultlessly, no matter when and where. As a consequence, it is becoming increasingly difficult to forge unique requirements regarding hardware issues and software support. This is particularly important in a multidisciplinary research and practice area such as WSNs, where close collaboration between users, application domain experts, hardware designers, and software developers is needed to implement efficient systems.In this chapter, who is who in WSNs are identified, motes, building blocks, producers, techniques, applications. A categorization of WSN applications according to their intended use is presented considering deployment, mobility, resources, cost, energy, heterogeneity, modality, infrastructure, topology, coverage, connectivity, size, lifetime, and QoS. The considered application categories, though non-exclusive, are branded as military, industrial, environmental, healthcare, daily life, and multimedia. Typical applications tasks are as follows:
Performance monitoring.
Surveillance.
Environmental monitoring.
Process control.
Tracking of personnel and goods.
Emergency management.
Robotics.
When compared with conventional mobile ad hoc networks (MANETs), WSNs have different characteristics and present different engineering challenges and considerations.KeywordsMilitary applications of WSNsIndustrial applications of WSNsEnvironmental applications of WSNsHealthcare applications of WSNsDaily life applications of WSNsMultimedia applications of WSNsRobotic WSNs
The devices forming Internet of Things (IoT) networks need to be re-programmed over the air, so that new features are added, software bugs or security vulnerabilities are resolved, and their applications can be re-purposed. The limitations of IoT devices, such as installation in locations with limited physical access, resource-constrained nature, large scale, and high heterogeneity, should be taken into consideration for designing an efficient and reliable pipeline for over-the-air programming (OTAP). In this work, we present a survey of OTAP techniques, which can be applied to IoT networks. We highlight the main challenges and limitations of OTAP for IoT devices and analyze the essential steps of the firmware update process, along with different approaches and techniques that implement them. In addition, we discuss schemes that focus on securing the OTAP process. Finally, we present a collection of state-of-the-art open-source and commercial platforms that integrate secure and reliable OTAP.
IoT devices can be used to complete a wide array of physical tasks, but due to factors such as low computational resources and distributed physical deployment, they are susceptible to a wide array of faulty behaviors. Many devices deployed in homes, vehicles, industrial sites, and hospitals carry a great risk of damage to property, harm to a person, or breach of security if they behave faultily. We propose a general fault handling system named IoTRepair, which shows promising results for effectiveness with limited latency and power overhead in an IoT environment. IoTRepair dynamically organizes and customizes fault-handling techniques to address the unique problems associated with heterogeneous IoT deployments. We evaluate IoTRepair by creating a physical implementation mirroring a typical home environment to motivate the effectiveness of this system. Our evaluation showed that each of our fault-handling functions could be completed within 100 milliseconds after fault identification, which is a fraction of the time that state-of-the-art fault-identification methods take (measured in minutes). The power overhead is equally small, with the computation and device action consuming less than 30 milliwatts. This evaluation shows that IoTRepair not only can be deployed in a physical system, but offers significant benefits at a low overhead.
A wireless sensor network is made up of extremely small autonomous units capable of sensing, computing and communicating. There are numerous restrictions on wireless sensor networks as the resource available to the wireless sensor network is limited. Thus, a number of clustering protocols in a routing sensor organization of sensor networks have been proposed in the literature which increase the throughput, save energy and decrease the delay in the system. In this paper, we put forward SNP, the one of its type link layer security architecture for wireless sensor networks. In this, the design vulnerabilities which were found in the protocols such as 802.11b and GSM are addressed using SNP. Security protocols have very conservative approach while guaranteeing the security and typically add up around 16-32 bytes as overhead. Owing to the scenario that sensor networks have limited supply of energy, little memory and low power processors, a 30 byte packet is more of unaffordable luxury for the wireless sensor networks. In SNP, the different trade-offs between separate cryptographic algorithms and wireless sensor network limitations are used to find an optimum point where packet overhead, security and resource requirements are met.
We study joint nonlinear state estimation with multi-period measurement vectors that are potentially corrupted by sparse gross errors. We consider a nonlinear sparse optimization formulation for joint sparse error correction and robust state estimation in a nonlinear sensing system wherein we exploit the sparsity and short-term invariance properties of gross error locations. We introduce a sequential convex approximation approach that can be used to solve the nonlinear sparse optimization problem with a convergence guarantee. We derive a necessary rank condition that identifiable gross error matrix should satisfy. Then, we present an identifiability-aware version of the proposed algorithm wherein we exploit the aforementioned identifiability condition to improve the accuracy of gross error localization. We demonstrate the efficacy of the proposed approach by applying it to power system nonlinear state estimation of IEEE 14-bus and 118-bus networks.
The presence of faults is inevitable in the Internet of Things (IoT) systems. Dependability in these systems is challenging due to the increasing level of dynamicity, heterogeneity, and complexity. IoT connects anything, anytime, and everywhere, introducing a complex relationship of interdependence, generating an increase in the susceptibility of the propagation of failures. The purpose of this study is to propose a pathology of failure in IoT Systems, exploring and characterizing faults, errors, failures, and their effects. This study investigates and classifies the source of faults, defines a taxonomy of the types of faults prone to happen, and defines the failure propagation model. As a result, the pathology establishes a common reference for fault, errors, and failures to be used by researchers and practitioners to improve tools for fault detection, fault diagnosis, fault tolerance, and fault handling in IoT Systems. This paper also proposes a failure propagation model for IoT systems that identify different combinations, paths, and fault-failure propagation effects.
WSNs are infiltrating the environment in its wide sense, indoors and outdoors, in the human body, in unapproachable emplacements; they have found their way into a wide variety of applications and systems with vastly varying requirements and characteristics. Guardian angels? Watchdogs? Whatever, they are intended to work properly, faultlessly, no matter when and where. As a consequence, it is becoming increasingly difficult to forge unique requirements regarding hardware issues and software support. This is particularly important in a multidisciplinary research and practice area such as WSNs, where close collaboration between users, application domain experts, hardware designers, and software developers is needed to implement efficient systems.
The field of IoT has blossomed and is positively influencing many application domains. In this paper, we bring out the unique challenges this field poses to research in computer systems and networking. The unique challenges arise from the unique characteristics of IoT systems such as the diversity of application domains where they are used and the increasingly demanding protocols they are being called upon to run (such as, video and LIDAR processing) on constrained resources (on-node and network). We show how these open challenges can benefit from foundations laid in other areas, such as, 5G cellular protocols, ML model reduction, and device-edge-cloud offloading. We then discuss the unique challenges for reliability, security, and privacy posed by IoT systems due to their salient characteristics which include heterogeneity of devices and protocols, dependence on the physical environment, and the close coupling with humans. We again show how the open research challenges benefit from reliability, security, and privacy advancements in other areas. We conclude by providing a vision for a desirable end state for IoT systems.
In the hostile areas, deployment of the sensor nodes in wireless sensor networks is one of the basic issue to be addressed. The node deployment method has great impact on the performance metrics like connectivity, security and resilience. In this paper, a technique based on strong keying mechanism is proposed which will enhance the security of a non-homogeneous network using the random deployment of the nodes. For this, the q-composite key pre-distribution technique is presented with new flavor that will enhance the network size as well as the security level in comparison to the existing techniques. The technique ensures the k-connectivity among the nodes with a redundant method to provide backup for failed nodes. In the simulation section, the performance of the proposed scheme is evaluated using NS-2 based upon the real model MICAz. A discussion based on various obtained results is also given in the paper.
The deployment of a wireless sensor network (WSN) is crucial to its reliability and performance. Yet, node placement is typically determined in-field via effort-demanding trial-and-error procedures, because existing approaches over-simplify the radio environment; this especially holds for forests, the focus of this article, where trees greatly affect communication.
We present LaPS ( L iDAR-assisted P lacement for wireless S ensor networks), an approach exploiting remote sensing to identify the best node placement automatically and prior to deployment. Airborne Light Detection and Ranging (LiDAR) data acquired for the target forest are automatically processed to estimate its properties (e.g., tree position and diameter) that, once incorporated into a specialized path loss model, enable per-link estimates of the radio signal attenuation induced by trees. Finally, a genetic algorithm explores placement options by evolving toward a (sub-)optimal solution while satisfying the user’s spatial and network requirements, whose formulation is very flexible and broadly applicable.
Our experiments, focused on a real forest, confirm that LaPS yields topologies of significantly higher quality w.r.t. approaches using a regular placement or a standard path loss model. Further, the ability to quickly explore the impact that changes in user requirements have on topology is invaluable to improve the operation of WSNs and reduce the effort of their in-field deployment.
A wireless sensor network (WSN) consists of hundreds to thousands of sensor nodes, working in any physical environment, and having sensing, computation and communication capabilities. Each sensor node in WSN is capable of communicating with each other and the base station (BS) for the purpose of data integration and dissemination. As the battery replacement is not easy for WSN with thousands of physically embedded nodes, energy conservation becomes one of the most important challenges in WSNs. And hence there is a need for energy efficient routing protocol to offer a long-life work time. In this paper, we propose an Advanced Tree Based Energy Routing Protocol. In this protocol for each round BS assigns a root node and broadcasts this selection to all sensor nodes. And then each node selects its parent by considering itself and its neighbour’s information, thus making it a dynamic protocol. It is a hierarchical protocol of WSN which increases the lifetime of network by using the energy of the network by using the energy of the network in an efficient way.
This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments.
Multi-hop wireless networks have a wide range of applications. In the practice of real applications, network deployment is a challenging task. Because deployment environment is complex, it is difficult to select suitable positions for node deployment, and the performance of deployed network cannot be guaranteed. This paper proposes a network deployment algorithm which aims to deploy a real network which has the same performance with the designed network. A deployment quality is defined to indicate whether a position is suitable for node deployment. When a position is unsuitable to deploy nodes, the algorithm gives information of a better deployment position. A simulation method based on network simulators is used to verify the proposed algorithm. According to our simulation results, the deployed network generated by the proposed algorithm can keep the performance of designed network including disconnected node number, connectivity, packet delivery ratio, and transmission delay.
Historically, the study of mountain hydrology and the water cycle has been largely observational, with meteorological forcing and hydrological variables extrapolated from a few infrequent manual measurements. Recent developments in Internet of Things (IoT) technology are revolutionizing the field of mountain hydrology. Low-power wireless sensor networks can now generate denser data in real-time and for a fraction of the cost of labor-intensive manual measurement campaigns. The American River Hydrological Observatory (ARHO) project has deployed thirteen low-power wireless IoT networks throughout the American River basin to monitor California’s snowpack. The networks feature a total of 945 environmental sensors, each reporting a reading every 15 minutes. The data reported is made available to the scientific community minutes after it is generated. This paper provides an in-depth technical description of the ARHO project. It details the requirements and different technical options, describes the technology deployed today, and discusses the challenges associated with large-scale environmental monitoring in extreme conditions.
As wireless sensor networks continue to grow, so does the need for effective security mechanisms. Because sensor networks may interact with sensitive data and/or operate in hostile unattended environments, it is imperative that these security concerns be addressed from the beginning of the system design. However, due to inherent resource and computing constraints, security in sensor networks poses different challenges than traditional network/computer security. There is currently enormous research potential in the field of wireless sensor network security. Thus, familiarity with the current research in this field will benefit researchers greatly. With this in mind, we survey the major topics in wireless sensor network security, present the obstacles and the requirements in the sensor security, classify many of the current attacks, and finally list their corresponding defensive measures.
Three species of small mammals, Mastacomys fuscus and Rattus fuscipes (both rodents), and Antechinus swainsonii (a small dasyrurid marsupial) live in the subalpine heathlands of southeastern Australia. This study records the climate and microclimate of these heathlands. Temperature was recorded at three sites at Smiggin Holes in Kosciusko National Park-just above the shrub layer, in a runway, and 20 cm below ground. Long-term meteorological data for ambient temperature, rainfall, and thickness and duration of snowpack are also presented. In summer, these small mammals experience temperatures of +5 to + 10°C while active and foraging at night, and temperatures of about + 10°C in burrows during the day. In winter, the snowpack provides good insulation resulting in a constant temperature of 0 to - 1°C in both runways and burrows regardless of the ambient air temperature above the snow. The climate and microclimate in the Australian Alps has many influences on the biology of small mammals; these include a short reproductive season, delay in the time to maturity and initiation of reproduction, reduced activity or torpor in winter, and relatively stable interannual population numbers.
We are developing an acoustic habitat-monitoring sensor network that recognizes and locates specific animal calls in real time. We investigate the system requirements of such a real-time acoustic monitoring network. We propose a system architecture and a set of lightweight collaborative signal processing algorithms that achieve real-time behavior while minimizing inter-node communication to extend the system lifetime. In particular, the target classification is based on spectrogram pattern matching while the target localization is based on beamforming using time difference of arrival (TDOA). We describe our preliminary implementation on a commercial off the shelf (COTS) testbed and present its performance based on testbed measurements.
The specification and management of quality of service (QoS) is important in networks and distributed computing systems, particularly to support multimedia applications. The advent of portable laptop computers, palmtops, and personal digital assistants with integrated communication capabilities facilitates mobile computing. This article is a survey of QoS concepts and techniques for mobile distributed computing environments. The requirements of current and future mobile computing are examined and the services required to support mobility are discussed. Generic concepts of QoS specification and management are overviewed followed by an analysis of the QoS work specific to mobile computing environments.
Over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. The field of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices for both scientific and commercial purposes. This paper examines the research decisions and design tradeoffs that arise when applying wireless peer-to-peer networking techniques in a mobile sensor network designed to support wildlife tracking for biology research.The ZebraNet system includes custom tracking collars (nodes) carried by animals under study across a large, wild area; the collars operate as a peer-to-peer network to deliver logged data back to researchers. The collars include global positioning system (GPS), Flash memory, wireless transceivers, and a small CPU; essentially each node is a small, wireless computing device. Since there is no cellular service or broadcast communication covering the region where animals are studied, ad hoc, peer-to-peer routing is needed. Although numerous ad hoc protocols exist, additional challenges arise because the researchers themselves are mobile and thus there is no fixed base station towards which to aim data. Overall, our goal is to use the least energy, storage, and other resources necessary to maintain a reliable system with a very high `data homing' success rate. We plan to deploy a 30-node ZebraNet system at the Mpala Research Centre in central Kenya. More broadly, we believe that the domain-centric protocols and energy tradeoffs presented here for ZebraNet will have general applicability in other wireless and sensor applications.
We investigate task decomposition and collaboration in a two-tiered sensor network for habitat monitoring. The system recognizes and localizes a specified type of birdcalls. The system has a few powerful macronodes in the first tier, and many less powerful micronodes in the second tier. Each macronode combines data collected by multiple micronodes for target classification and localization. We describe two types of lightweight preprocessing which significantly reduce data transmission from micronodes to macronodes. Micronodes classify events according to their cross-zero rates and discard irrelevant events. Data about events of interest is reduced and compressed before being transmitted to macronodes for target localization. Preliminary experiments illustrate the effectiveness of event filtering and data reduction at micronodes.
Spatial localization or the ability to locate nodes is an important building block for next generation pervasive computing systems, but a formidable challenge, particularly, for very small hardware and energy constrained devices, for noisy, unpredictable environments and for very large ad hoc deployed and networked systems. In this paper, we describe, validate and evaluate in real environments a very simple self localization methodology for RF-based devices based only on RF-connectivity constraints to a set of beacons (known nodes), applicable outdoors. Beacon placement has a significant impact on the localization quality in these systems. To self-configure and adapt the localization in noisy environments with unpredictable radio propagation vagaries, we introduce the novel concept of adaptive beacon placement. We propose several novel and density adaptive algorithms for beacon placement and demonstrate their effectiveness through evaluations. We also outline an approach in which beacons leverage a software controllable variable transmit power capability to further improve localization granularity. These combined features allow a localization system that is scalable and ad hoc deployable, long-lived and robust to noisy environments. The unique aspect of our localization approach is our emphasis on adaptive selfconfiguration. 1
Sensor networks are distributed event-based systems that differ from traditional communication networks in several ways: sensor networks have severe energy constraints, redundant low-rate data, and many-to-one flows. Datacentric mechanisms that perform in-network aggregation of data are needed in this setting for energy-efficient information flow. In this paper we model data-centric routing and compare its performance with traditional end-toend routing schemes. We examine the impact of sourcedestination placement and communication network density on the energy costs and delay associated with data aggregation. We show that data-centric routing offers significant performance gains across a wide range of operational scenarios. We also examine the complexity of optimal data aggregation, showing that although it is an NP-hard problem in general, there exist useful polynomial-time special cases. 1
We are developing an acoustic habitat-monitoring sensor network that recognizes and locates specific animal calls in real time. In this paper, we investigate the system requirements of such a real-time acoustic monitoring network. We propose a system architecture and a set of lightweight collaborative signal processing algorithms that achieve real-time behavior while minimizing inter-node communication to extend the system lifetime. In particular, the target classification is based on spectrogram pattern matching while the target localization is based on beamforming using Time Difference Of Arrival (TDOA). We describe our preliminary implementation on a Commercial Off The Shelf (COTS) testbed and present its performance based on testbed measurements.
Wireless ad hoc sensor networks have the advantage of spanning a large geographical region and being able to collaboratively detect and track non-local spatio-temporal events. This paper presents a dual-space approach to event tracking and sensor resource management in sensor networks. The dual-space transformation maps a non-local phenomenon, e.g., the edge of a half-plane shadow, to a single point in the dual space, and maps locations of distributed sensor nodes to a set of lines that partitions the dual space. The detection problem becomes finding and tracking the cell that contains the point in the arrangement defined by these lines. This mechanism can be effectively used for power management of the sensor network -- nodes that will not be immediately visited by an event can be turned off to save energy required for sensing, processing, and communication. The approach has been successfully demonstrated on a laboratory testbed built using the UC Berkeley motes sensors. An implemented application of detecting and tracking light shadow edges moving over a sensor field is described.
We provide an in-depth study of applying wireless sensor networks to real-world habitat monitoring. A set of system design requirements are developed that cover the hardware design of the nodes, the design of the sensor network, and the capabilities for remote data access and management. A system architecture is proposed to address these requirements for habitat monitoring in general, and an instance of the architecture for monitoring seabird nesting environment and behavior is presented. The currently deployed network consists of 32 nodes on a small island o# the coast of Maine streaming useful live data onto the web. The applicationdriven design exercise serves to identify important areas of further work in data sampling, communications, network retasking, and health monitoring.
As new fabrication and integration technologies reduce the cost and size of micro-sensors and wireless interfaces, it becomes feasible to deploy densely distributed wireless networks of sensors and actuators. These systems promise to revolutionize biological, earth, and environmental monitoring applications, providing data at granularities unrealizable by other means. In addition to the challenges of miniaturization, new system architectures and new network algorithms must be developed to transform the vast quantity of raw sensor data into a manageable stream of high-level data. To address this, we propose a tiered system architecture in which data collected at numerous, inexpensive sensor nodes is filtered by local processing on its way through to larger, more capable and more expensive nodes. We briefly describe Habitat monitoring as our motivating application and introduce initial system building blocks designed to support this application. The remainder of the paper presents detail...
Technological progress in integrated, low-power, CMOS communication devices and sensors makes a rich design space of networked sensors viable. They can be deeply embedded in the physical world and spread throughout our environment like smart dust. The missing elements are an overall system architecture and a methodology for systematic advance. To this end, we identify key requirements, develop a small device that is representative of the class, design a tiny event-driven operating system, and show that it provides support for e#cient modularity and concurrency-intensive operation. Our operating system fits in 178 bytes of memory, propagates events in the time it takes to copy 1.25 bytes of memory, context switches in the time it takes to copy 6 bytes of memory and supports two level scheduling. The analysis lays a groundwork for future architectural advances. 1. INTRODUCTION As the post-PC era emerges, several new niches of computer system design are taking shape with characteristics...
Continuous generations of Frankliniella occidentalis (Pergande) and F. fusca (Hinds) develop through the winter and spring in northern Florida on plant hosts such as hairy vetch, Vicia villosa Roth. Previously reported research compared development under field conditions of these thrips to predictions of temperature-dependent developmental models obtained in laboratory experiments and concluded that accumulated degree-days of ambient temperatures recorded at a nearby national weather station underestimated development of populations developing under field conditions. Thus, the objective of this study was to compare ambient temperatures to microclimate temperatures in V. villosa plots and its effect on thrips development. An electronic data logger was used in this experiment to continuously record over 63 d ambient, upper plant canopy, middle plant height, lower plant height, and soil temperatures in plots of V. villosa. The microclimatic temperatures and their degree-day accumulations, based on daily maximum and minimum records, were significantly greater (P = 0.05) than the ambient temperature and degree-day accumulations obtained from a nearby National Oceanic and Atmospheric Administration (NOAA) weather station. There were no significant differences in mean temperature and degree-day accumulations within the upper, middle and lower portions of V. villosa plants. Based on degree-day accumulations in the upper plant canopy, 3.1 generations were predicted for F. occidentalis and 2.4 generations for F. fusca during the study. However, using the NOAA degree-day accumulations, only 2.5 and 1.9 generations were predicted, respectively. During this study, an accumulated discrepancy of 3/4 of a generation was calculated for F. occidentalis and more than half of a generation for F. fusca between the NOAA weather data and the microclimate data. Thus, ambient temperatures obtained from the NOAA weather station would underestimate development, as was observed and reported previously. The results demonstrated the importance of using microclimatic measurements, rather than ambient records, for best estimating developmental potential of thrips.
Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm for such coordination. Directed diffusion is datacentric in that all communication is for named data. All nodes in a directed diffusion-based network are application-aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network. We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network.
This paper presents Span, a power saving technique for multi-hop ad hoc wireless networks that reduces energy consumption without significantly diminishing the capacity or connectivity of the network. Span builds on the observation that when a region of a shared-channel wireless network has a sufficient density of nodes, only a small number of them need be on at any time to forward traffic for active connections. Span is a distributed, randomized algorithm where nodes make local decisions on whether to sleep, or to join a forwarding backbone as a coordinator. Each node bases its decision on an estimate of how many of its neighbors will benefit from it being awake, and the amount of energy available to it. We give a randomized algorithm where coordinators rotate with time, demonstrating how localized node decisions lead to a connected, capacity-preserving global topology. Improvement in system lifetime due to Span increases as the ratio of idle-to-sleep energy consumption increases, and increases as the density of the network increases. For example, our simulations show that with a practical energy model, system lifetime of an 802.11 network in power saving mode with Span is a factor of two better than without. Span integrates nicely with 802.11 - when run in conjunction with the 802.11 power saving mode, Span improves communication latency, capacity, and system lifetime.
Low-power integration of sensing, communication, and computation requires a new approach to wireless design. Flexible interfaces and primitive accelerators enable aggressive system-level optimizations. Mica's flexible design serves as a building block for creating efficient application-specific protocols. Instead of defining narrow, standardized application interfaces, Mica provides a set of richly interconnected primitives (such as data serializers and timing extractors) to facilitate cross-layer optimizations. To explore novel systems approaches, researchers can develop customized protocols tailored to their application; Mica does not require use of predefined protocols.
We present the Tiny AGgregation (TAG) service for aggregation in low-power, distributed, wireless environments. TAG allows users to express simple, declarative queries and have them distributed and executed efficiently in networks of low-power, wireless sensors. We discuss various generic properties of aggregates, and show how those properties affect the performance of our in network approach. We include a performance study demonstrating the advantages of our approach over traditional centralized, out-of-network methods, and discuss a variety of optimizations for improving the performance and fault-tolerance of the basic solution.
Wireless sensor networks involve very large numbers of small, low-power, wireless devices. Given their unattended nature, and their potential applications in harsh environments, we need a monitoring infrastructure that indicates system failures and resource depletion. We describe an architecture for sensor network monitoring, then focus on one aspect of this architecture: continuously computing aggregates (sum, average, count) of network properties (loss rates, energy-levels etc., packet counts). Our contributions are two-fold. First, we propose a novel tree construction algorithm that enables energy-efficient computation of some classes of aggregates. Second, we show through actual implementation and experiments that wireless communication artifacts in even relatively benign environments can significantly impact the computation of these aggregate properties. In some cases, without careful attention to detail, the relative error in the computed aggregates can be as much as 50%. However, by carefully discarding links with heavy packet loss and asymmetry, we can improve accuracy by an order of magnitude.
Sensor networks are distributed event-based systems that differ from traditional communication networks in several ways: sensor networks have severe energy constraints, redundant low-rate data, and many-to-one flows. Data-centric mechanisms that perform in-network aggregation of data are needed in this setting for energy-efficient information flow. In this paper we model data-centric routing and compare its performance with traditional end-to-end routing schemes. We examine the impact of source-destination placement and communication network density on the energy costs and delay associated with data aggregation. We show that data-centric routing offers significant performance gains across a wide range of operational scenarios. We also examine the complexity of optimal data aggregation, showing that although it is an NP-hard problem in general, there exist useful polynomial-time special cases.
Advances in processor, memory, and radio technology enable small and cheap nodes capable of sensing, communication, and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. We explore the directed diffusion paradigm for such coordination. Directed diffusion is data-centric in that all communication is for named data. All nodes in a directed-diffusion-based network are application aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network (e.g., data aggregation). We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network analytically and experimentally. Our evaluation indicates that directed diffusion can achieve significant energy savings and can outperform idealized traditional schemes (e.g., omniscient multicast) under the investigated scenarios.
We provide an in-depth study of applying wireless sensor networks to real-world habitat monitoring. A set of system design requirements were developed that cover the hardware design of the nodes, the design of the sensor network, and the capabilities for remote data access and management. We propose a system architecture that addresses these requirements for habitat monitoring in general. We present an in-depth discussion of the implementation of the architecture for habitat monitoring. In the summer of 2002, 32 nodes were deployed on a small island off the coast of Maine streaming useful live data onto the web using our implementation. Results from the deployment show the profound impact software and hardware power management has on node longevity. The effectiveness of the system architecture is shown through the packet throughput and through the delivery of over 1.2 million readings logged at our database in Berkeley. The system operated for over four months; it provided data for two months after researchers had left the island for the winter due to poor weather conditions. The application-driven design exercise serves to identify important areas of further work in power management, data sampling, communications, network retasking, and health monitoring. We discuss the lessons learned from our deployment and provide a series of solutions that include new hardware, software, and protective enclosures.
Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diusion paradigm for such coordination. Directed diusion is datacentric in that all communication is for named data. All nodes in a directed diusion-based network are applicationaware. This enables diusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network. We explore and evaluate the use of directed diusion for a simple remote-surveillance sensor network. 1 Introduction In the near future, advances in processor, memory and radio technology will enable small and cheap nodes capable of wireless communication and signicant computation. The addition of sensing capability to such devices will make distributed microsensing|an activity in which a collection of ...
Sensor networks, a novel paradigm in distributed wireless communication technology, have been proposed for use in various applications including military surveillance and environmental monitoring. These systems could deploy heterogeneous collections of sensors capable of observing and reporting on various dynamic properties of their surroundings in a time sensitive manner. Such systems suffer bandwidth, energy, and throughput constraints that limit the quantity of information transferred from end to end. These factors coupled with unpredictable traffic patterns and dynamic network topologies make the task of designing optimal protocols for such networks difficult. Mechanisms to perform data centtic aggregation utilizing application specific knowledge provide a means to augmenting throughput, but have limitations due to their lack of adaptation and reliance on application specific decisions. lye therefore propose a novel aggregation scheme that adaptively performs application independent data aggregation in a time sensitive manner. Our work isolates aggregation decisions into a module that resides between the network and the data link layer and does not require any modifications to the currently existing MAC and network layer protocols. lYe take advantage of queuing delay and the broadcast nature of wireless communication to concatenate network units into an aggregate using a novel adaptive feedback scheme to schedule the delivery of this aggregate to the MAC layer for transmission. In our evaluation we show that end-to-end transmission delay is reduced by as much as 80% under heavy traffic loads. Additionally, we show as much as a 50% reduction in transmission energy consumption with the addition of only 2 bytes of header overhead per network unit. Theoretical analysis,...
Numerous factors contribute to errors in sensor measurements. In order to be useful, any sensor device must be calibrated to adjust its accuracy against the expected measurement scale. In large-scale sensor networks, calibration will be an exceptionally difficult task since sensor nodes are often not easily accessible and manual device-by-device calibration is intractable. In this paper, we present a two-phase post-deployment calibration technique for large-scale, dense sensor deployments. In its first phase, the algorithm derives relative calibration relationships between pairs of co-located sensors, while in the second phase, it maximizes the consistency of the pair-wise calibration functions among groups of sensor nodes. The key idea in the first phase is to use temporal correlation of signals received at neighboring sensors when the signals are highly correlated (i.e. sensors are observing the same phenomenon) to derive the function relating their bias in amplitude. We formulate the second phase as an optimization problem and present an algorithm suitable for localized implementation. We evaluate the performance of the first phase of the algorithm using empirical and simulated data.
Wireless sensor networks involve very large numbers of small, low-power, wireless devices. Given their unattended nature, and their potential applications in harsh environments, we need a monitoring infrastructure that indicates system failures and resource depletion. In this paper, we briefly describe an architecture for sensor network monitoring, then focus on one aspect of this architecture: continuously computing aggregates (sum, average, count) of network properties (loss rates, energylevels etc., packet counts). Our contributions are two-fold. First, we propose a novel tree construction algorithm that enables energy-efficient computation of some classes of aggregates. Second, we show through actual implementation and experiments that wireless communication artifacts in even relatively benign environments can significantly impact the computation of these aggregate properties. In some cases, without careful attention to detail, the relative error in the computed aggregates can be as much as 50%. However, by carefully discarding links with heavy packet loss and asymmetry, we can improve accuracy by an order of magnitude.
We describe an ad-hoc localization system for sensor networks and explain why traditional calibration methods are inadequate for this system. Building upon previous work, we frame calibration as a parameter estimation problem; we parameterize each device and choose the values of those parameters that optimize the overall system performance. This method reduces our average error from 74.6% without calibration to 10.1%. We propose ways to expand this technique to a method of autocalibration for localization as well as to other sensor network applications.
We introduce a geographical adaptive delity (GAF) algorithm that reduces energy consumption in ad hoc wireless networks. GAF conserves energy by identifying nodes that are equivalent from a routing perspective and then turning o unnecessary nodes, keeping a constant level of routing delity. GAF moderates this policy using application- and system-level information; nodes that source or sink data remain on and intermediate nodes monitor and balance energy use. GAF is independent of the underlying ad hoc routing protocol; we simulate GAF over unmodied AODV and DSR. Analysis and simulation studies of GAF show that it can consume 40% to 60% less energy than an unmodi ed ad hoc routing protocol. Moreover, simulations of GAF suggest that network lifetime increases proportionally to node density; in one example, a four-fold increase in node density leads to network lifetime increase for 3 to 6 times (depending on the mobility pattern). More generally, GAF is an example of adaptive delity, a technique proposed for extending the lifetime of self-conguring systems by exploiting redundancy to conserve energy while maintaining application delity. 1.
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