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Embedding the Internet: Wireless integrated network sensors
... Researchers have devised many protocols for communication, and security in wireless networks life infrastructure based networks, ad-hoc networks, mobile networks etc [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. But as mentioned above, these protocols cannot be used directly due to resource constraints of sensor nodes for resources like limited battery power, communication capability, and computational speed. ...
... These are not suitable for area monitoring applications. Battery power of individual sensor nodes is a precious resource in the WSN [4][5]. For example, the power consumed by a Berkeley mote to transmit 1-bit of data is equivalent to the computation of 800m instructions [4]. ...
Radio transmission and reception consumes a lot of energy in a wireless sensor network (WSN), which are made of low-cost, low-power, small in size, and multifunctional sensor nodes. Thus, one of the important issues in wireless sensor network is the inherent limited battery power within the sensor nodes. Therefore, battery power is crucial parameter in the algorithm design in maximizing the lifespan of sensor nodes. It is also preferable to distribute the energy dissipated throughout the wireless sensor network in order to maximize overall network performance. Much research has been done in recent years in the area of low power routing protocol, but, there are still many design options open for improvement, and for further research targeted to the specific applications, need to be done. In this paper, we propose a new approach of an energy-efficient homogeneous clustering algorithm for wireless sensor networks in which the lifespan of the network is increased by ensuring a homogeneous distribution of nodes in the clusters. In this clustering algorithm, energy efficiency is distributed and network performance is improved by selecting cluster heads on the basis of (i) the residual energy of existing cluster heads, (ii) holdback value, and (iii) nearest hop distance of the node. In the proposed clustering algorithm, the cluster members are uniformly distributed and the life of the network is further extended.
... For some application location accuracy is more important apart from lifetime. According to [12][13] deploying less complex and many sensor nodes in close proximity of the phenomenon make WSN simpler and energy efficient. According to researchers WSNs support various existing application areas as explained in section II and have potential to support entirely new applications. ...
... WSN in different types of applications. List of applications supported by WSNs is listed as below and its detailed description is available in [10][11][12][13][14][15][17][18][19][20][21][22][23][24][25][26][27][28][29] One of the most important applications of WSN is during disaster relief. For example during wildfire situation relief team can drop sensor nodes loaded with thermal sensor from airplane into affected area. ...
... An application layer management protocol makes the hardware and softwares of the lower layers transparent to the sensor network management applications. System administrators interact with sensor networks by using SMP[3] . Unlike many other networks, sensor networks consist of nodes that do not have global identification, and they are usually infrastructureless. ...
... Hence, Mary modulation gains are significant only for low startup power systems. This low power architecture [3] can be mapped to an applicationspecific integrated circuit technology to further improve efficiency. The Ultra Wideband (UWB) or impulse radio has been used for baseband pulse radar and ranging systems and has recently drawn considerable interest for communication applications, especially in indoor wireless networks . ...
This Book presents the various newest works in Topology of control for the wireless Sensor Network, which aims to save the life time of each Sensor and a better performance communication. The book also contains an introduction to the world of sensor networks with some examples of applications through the transport and physical layer, however, its presents also a descriptive part of Attariya simulator designed for the Topology of control.
... An application layer management protocol makes the hardware and softwares of the lower layers transparent to the sensor network management applications. System administrators interact with sensor networks by using SMP[3] . Unlike many other networks, sensor networks consist of nodes that do not have global identification, and they are usually infrastructureless. ...
... Hence, Mary modulation gains are significant only for low startup power systems. This low power architecture [3] can be mapped to an applicationspecific integrated circuit technology to further improve efficiency. The Ultra Wideband (UWB) or impulse radio has been used for baseband pulse radar and ranging systems and has recently drawn considerable interest for communication applications, especially in indoor wireless networks . ...
This Book presents the various newest works in Topology of control for the wireless Sensor Network, which aims to save the life time of each Sensor and a better performance communication. The book also contains an introduction to the world of sensor networks with some examples of applications through the transport and physical layer, however, it present also a descriptive part of Attariya simulator designed for the Topology of control
... An application layer management protocol makes the hardware and softwares of the lower layers transparent to the sensor network management applications. System administrators interact with sensor networks by using SMP[3] . Unlike many other networks, sensor networks consist of nodes that do not have global identification, and they are usually infrastructureless. ...
... Hence, Mary modulation gains are significant only for low startup power systems. This low power architecture [3] can be mapped to an applicationspecific integrated circuit technology to further improve efficiency. The Ultra Wideband (UWB) or impulse radio has been used for baseband pulse radar and ranging systems and has recently drawn considerable interest for communication applications, especially in indoor wireless networks . ...
This Book presents the various newest works in Topology of control for the wireless Sensor Network, which aims to save the life time of each Sensor and a better performance communication. The book also contains an introduction to the world of sensor networks with some examples of applications through the transport and physical layer, however, it present also a descriptive part of Attariya simulator designed for the Topology of control
... An application layer management protocol makes the hardware and softwares of the lower layers transparent to the sensor network management applications. System administrators interact with sensor networks by using SMP[3] . Unlike many other networks, sensor networks consist of nodes that do not have global identification, and they are usually infrastructureless. ...
... Hence, Mary modulation gains are significant only for low startup power systems. This low power architecture [3] can be mapped to an applicationspecific integrated circuit technology to further improve efficiency. The Ultra Wideband (UWB) or impulse radio has been used for baseband pulse radar and ranging systems and has recently drawn considerable interest for communication applications, especially in indoor wireless networks . ...
This Book presents the various newest works in Topology of control for the wireless Sensor Network, which aims to save the life time of each Sensor and a better performance communication. The book also contains an introduction to the world of sensor networks with some examples of applications through the transport and physical layer, however, it also contains a descriptive part of Attariya simulator designed for the Topology of control.
... MP versions of AMP (MP- AMP) for MP-CS have been studied in the literature [13, 16]. Usually, MP platforms are designed for distributed settings such as sensor networks [17, 18] or large-scale " big data " computing systems [19]. We reduce the communication costs of MP platforms by applying lossy compression [20][21][22]to the communication portion of MP-AMP. ...
... when communication costs are low [26] (examples are commerical cloud computing systems [19], multi-processor CPUs, and graphic processing units), whereas more iterations allow to reduce the coding rate when communication is costly [26] (for example, in sensor networks [17, 18]). ...
We consider large-scale linear inverse problems in Bayesian settings. Our general approach follows a recent line of work that applies the approximate message passing (AMP) framework in multi-processor (MP) computational systems by storing and processing a subset of rows of the measurement matrix along with corresponding measurements at each MP node. In each MP-AMP iteration, nodes of the MP system and its fusion center exchange lossily compressed messages pertaining to their estimates of the input. There is a trade-off between the physical costs of the reconstruction process including computation time, communication loads, and the reconstruction quality, and it is impossible to simultaneously minimize all the costs. We pose this minimization as a multi-objective optimization problem (MOP), and study the properties of the best trade-offs (Pareto optimality) in this MOP. We prove that the achievable region of this MOP is convex, and conjecture how the combined cost of computation and communication scales with the desired mean squared error. These properties are verified numerically.
... Large companies such as Symns, Philips, Intel, too, was interested in this technology and try to develop sensors with their own designs. Considerable standardization activities in the field of sensor networks is being done[2].Important that it be noted that the standard 802.15.4 MAC and physical layer protocol for applications such as remote control and sensor networks are2 8 T 4 0 T 2 8 T 4 0 T assimilating. ZigBee industrial companies, including more than 100 members from 22 countries of four continents of the world are working to improve the standard 802.12.4.With all the efforts in the field of sensor networks, there are still issues with slow growth of these networks are built. ...
... At any moment, a node can be removed from the network or the network topology changes. In such networks it is necessary that the sensor data, are stored in the way that can be transmitted via the Web[2][3][4][5][6][7][8]. -It is also possible the sampling rate in sensor networks will change[1,9,10]. ...
... A location-based scheme that protects the rest of a network, even when parts of the network are compromised. Our approach to communication security in sensor networks is based on a principle stated in [12] that says that data items must be protected to a degree consistent with their value. In the particular architecture [4], for which we are developing our communication security scheme, we differentiate between three types of data sent through the network: 1. Mobile code 2. Locations of sensor nodes 3. Application specific data Following this categorization, we specify the main security threats and the appropriate security mechanisms: ...
The Networks of wireless micro sensors for monitoring physical environments have emerged as an important new application area for wireless technology. Key attributes of these new types of networked systems are the severely constrained computational and energy resources and an ad hoc operational environment. This paper is a study of the communication security aspects of these networks. Resource limitations and specific architecture of sensor networks call for customized security mechanisms. Our approach is to classify the types of data existing in sensor networks, and identify possible communication security threats according to that classification. We propose a communication security scheme where for each type of data we define a corresponding security mechanism. By employing this multitier security architecture where each mechanism has different resource requirements, we allow for efficient resource management, which is essential for wireless sensor networks.
... It can also connect to the Internet by wire or wireless. Nowadays, WSN s have been widely used in disaster forecasting, national defense and military, environmental monitoring and other fields with a huge market application prospect [2][3][4][5]. We need the routing protocol in the WSN to guarantee the data is accurately and efficiently transferred from the source node to the destination node [6]. ...
To better collect data in context to balance energy consumption, wireless sensor networks (WSN) need to be divided into clusters. The division of clusters makes the network become a hierarchical organizational structure, which plays the role of balancing the network load and prolonging the life cycle of the system. In clustering routing algorithm, the pros and cons of clustering algorithm directly affect the result of cluster division. In this paper, an algorithm for selecting cluster heads based on node distribution density and allocating remaining nodes is proposed for the defects of cluster head random election and uneven clustering in the traditional LEACH protocol clustering algorithm in WSN. Experiments show that the algorithm can realize the rapid selection of cluster heads and division of clusters, which is effective for node clustering and is conducive to equalizing energy consumption.
... The recent technological advancements in the field of micro electrical mechanical systems (MEMS) have made the manufacturing and use of small, low powered and moderate cost micro-sensors [1][2][3][4][5] both technically and economically feasible. A Wireless Sensor Network (WSN) [6][7][8][9][10][11][12] consists of hundreds to thousands of low-power multi-functioning sensor nodes, operating in an unattended environment, having capabilities of sensing, computation and communications. Basically, a sensor node is a microelectro-mechanical system [MEMS] and it can sense the environment periodically, fuse data if required and broadcast data to some other node. ...
The nodes in a sensor network are severely constrained by energy. Reducing the energy consumption of the nodes to prolong the network lifetime is considered a critical challenge while designing a new routing protocol. In this paper we propose a new power-aware, adaptive, hierarchical and chain based protocol - CCPAR (Clustered Chain based Power Aware Routing) that utilizes the periodic assignments of the cluster head role to different nodes based on the highest residual battery capacity for ensuring the even dissipation of power by all the nodes. Transmission from a single cluster head to the base station in each round and the distribution of the data aggregation workload among all the nodes, save the cluster heads from early exhaustion. The use of data aggregation also reduces the amount of information to be transmitted to the base station. By chaining the nodes in each cluster and using a separate chain for the cluster heads, CCPAR offers the advantage of small transmit distances for most of the nodes and thus helps them to be operational for a longer period of time by conserving their limited energy. The simultaneous construction of multiple chains in different clusters reduces the time for chain construction as well as the length of each of the chains. These shorter length chains solve the problem of excessive delay in transmission for the distant nodes. Use of a fresh set of parameter values in each round provides the users the flexibility to change these values in a way to control the power consumption. The introduction of MAX threshold enables CCPAR to be quickly responsive and thus highly suitable for time critical applications. From the performance evaluation we observe that CCPAR outperforms other protocols in terms of energy saving and longevity of the network.
... Since the sensor nodes have limited energy supply, energy plays an important role in the establishment and operation of the network. And the energy for sending and receiving data is far greater than the energy for calculation [39]. Therefore, how to effectively reduce the energy consumption in communication is an urgent issue. ...
With the rapid development of the Internet of Things technology, wireless sensor networks as the core technique have been applied in military, precision agriculture, security monitoring, intelligent traffic, instrument monitoring and so on. In wireless sensor networks with mobile sinks, the sensor nodes have limited energy supply and the sink is removable. To improve the network efficiency and the sink utilization, we present a cluster tree-based energy-efficient routing protocol (CTEER). The protocol is based on rendezvous which is capable of reducing the latency. CTEER firstly plans the mobile path for the sink and creates a cross-communication region. Then, a cross-routing tree with the mobile sink as the center is constructed within the region. The routing tree changes with the location of the sink in each round so that the utilization rate of sensor nodes can be improved. Meanwhile, we divide the ordinary nodes outside the cross-region into multiple clusters. The ordinary nodes can send data to the routing tree directly through the cluster heads. In this way, transmission hops from ordinary nodes to the routing tree can be decreased. Thus, the data latency can be reduced. Experimental results show that CTEER protocol keeps competitive in terms of energy saving, network lifetime and data latency reduction. In four experimental environments, compared with RRP, the total energy consumption of nodes in each round in CTEER is decreased by 77.58%, 62.03%, 57.01% and 50.95%, respectively. In three experimental environments, compared with FRM, the total energy consumption of nodes in each round in CTEER is reduced by 35.04%, 29.93% and 4.08%, respectively. Compared with RRP, the total hops of sensor nodes in each round in CTEER are reduced by 82.44%, 75.56%, 74.16% and 78.04%, respectively. Compared with FRM, the hops are decreased by 43.25%, 40.19%, 39.10% and 39.64%, respectively. Considering the low delay advantage, CTTEER is suitable for time-sensitive applications. Some examples of the applications would be target tracking, telemonitoring of human health status and artificial intelligence applications.
... Some of the commercial applications are tracking and detection of vehicles; monitoring material fatigue; environmental control in office buildings; interactive museums; building virtual keyboards; machine diagnosis; automation and factory process control; inventory managing; smart structures with sensor nodes embedded inside; interactive toys; car thefts monitoring and detecting; product quality monitoring; constructing smart office spaces; factory instrumentation; transportation; local control of actuators; robot control and guidance in automatic manufacturing environments; monitoring disaster area; and instrumentation of semiconductor processing chambers, rotating machinery, wind tunnels, and anechoic chambers [40,39,92,91,98,5,30]. ...
Effective maintenance of an industrial device can only be based on the reliability and accuracy of physical data captured on said device for monitoring purposes. In some cases, monitoring of such industrial systems or areas to be monitored can not be ensured by individual or wire sensors, for example due to access problems or hostile environments. Wireless Sensor Networks (RCSF) are an alternative. Due to the nature of the communications in these networks, and the characteristics of the devices making up the latter, an RCSF is at high risk of failures at the sensors, and in this case the loss of various data is likely - problematic for the monitoring of the device. To study the relevance of the RCSF to the so-called Prognostic and Health Management (PHM) process used to determine the maintenance plan for a device to be monitored, and the impact of the various strategies deployed in the latter on the latter, proposed a first efficient diagnostic algorithm and used it in a simulated RCSF to measure its performance (this simulator being a program that we developed).
... This algorithm divides the sensing field into a number of uniform cells that depends on the total number of sensor nodes. To calculate the desired number of sub-cells and thus the number of cluster heads they utilize the same heuristics of the LEACH algorithm [10] which consider a 5% of the total number of sensor nodes. VGDRA algorithm uses the nodes that have the least distance to the center of each cell to operate as a cluster head. ...
Based on the wide variety of applications of wireless sensor networks (WSNs) in different aspects of life, research focusing on WSNs have rapidly increased in the recent few years. Different challenges shorten the operation of sensor nodes over the targeted area for different reasons such as danger, inhospitality, and limited energy resources of the surrounding area. One major issue is the energy required to operate the individual sensor nodes that definitely affect the operation of the entire sensor network. Accordingly, energy consumption must be minimized as possible which requires to compromise sensor network activities as well as network operation. One fundamental solution commonly used for minimizing the energy consumption in each sensor node is using an energy-efficient routing algorithm. In this study, a routing approach depends on the grid topology of the sensor network is presented to maximize the lifetime of WSNs via balancing a load of data traffic among sensor nodes as evenly as possible. The evaluation process is done using CFDASC routing protocol since it represents the most comparable and related algorithm among previous work. Simulation results prove that the presented approach outperformance CFDASC algorithm in terms of network stability and load balancing of the entire network.
... However, most research work only concerns energy saving, which is necessary but cannot guarantee prolonging the network lifetime. So we set the objective function as fomula (5). ...
It is quite common that the existing communication facilities are damaged or destroyed in a disaster. Wireless ad-hoc network is a distributed wireless network system which does not rely on any fixed infrastructures and is capable of self-adaption to the dramatic network changes and thus has been wildly used in emergency communications. Recently, many researchers have tried to introduce NDN [1] techniques into such context, showing unparallel advantages in terms of throughput, delay, reliability, etc. This paper focuses on a particularly interesting issue in an NDN based wireless ad-hoc network, that is how to maximize the lifecycle of an NDN emergency ommunication network given
limited power at each node. We proved, in many scenarios, that
the unbalanced energy consumption in an NDN based wireless
ad-hoc network generally is more serious than that of in an IPbased
one, due to the existence of cache. Thereafter, we proposed
a novel energy-saving caching and forwarding scheme to achieve
better energy load balancing using CS popularity increment
table(CPIT) as its indicator. Our simulation experiment with
ndnSIM2.0 [3] on a topology generated by BRITE indicates that
the proposed scheme can significantly extend the life span of a
network by 32% or 58% in contrast to the native NDN scheme,
respectively, under two different application scenarios.
keywords—Named Data Networking, Wireless Ad-Hoc Networks,
Energy Saving, Load Balancing, Forwarding Strategy
... Some budding applications of wireless sensor networks are wildlife habit study, environmental observation and health care monitoring. Since wireless sensor nodes are power-constrained devices, long-haul transmissions should be kept to minimum in order to expand the network lifetime [3][4][5][6]. Thus, direct communications between nodes and the base station are not intensely encouraged. ...
A wireless sensor network is subject to a unique set of resource constraints such as finite battery power and constrained network communication bandwidth. Each sensor node has a microprocessor and a petite amount of memory. Also every sensor node is equipped with one or more sensing devices such as acoustic sensors, microphone arrays, video cameras, infrared, seismic or magnetic sensors. But it is difficult to replace the deceased batteries of the sensor nodes. A distinctive sensor node consumes much of its energy during wireless communication. This research work suggests the development of a hierarchical distributed clustering mechanism, which gives improved performance over the existing clustering algorithm LEACH. The two hiding concepts behind the proposed scheme are the hierarchical distributed clustering mechanism and the concept of threshold. Energy utilization is significantly reduced, thereby greatly prolonging the lifetime of the sensor nodes.
... Clustering [2][3][4][5][6][7] is an effectual topology control approach, which can prolong the lifetime and increase scalability for these sensor networks. The popular criterion for clustering technique (figure 2) is to select a cluster head (CH) with more residual energy and to spin them periodically. ...
Latest researches in wireless communications and electronics has imposed the progress of low-cost wireless sensor nodes. Clustering is a thriving topology control approach, which can prolong the lifetime and increase scalability for wireless sensor networks. The admired criteria for clustering methodology are to select cluster heads with more residual energy and to rotate them periodically. Sensors at heavy traffic locations quickly deplete their energy resources and die much earlier, leaving behind energy hole and network partition. In this paper, a model of distributed layer-based clustering algorithm is proposed based on three concepts. First, the aggregated data is forwarded from cluster head to the base station through cluster head of the next higher layer with shortest distance between the cluster heads. Second, cluster head is elected based on the clustering factor, which is the combination of residual energy and the number of neighbors of a particular node within a cluster. Third, each cluster has a crisis hindrance node, which does the function of cluster head when the cluster head fails to carry out its work in some critical conditions. The key aim of the proposed algorithm is to accomplish energy efficiency and to prolong the network lifetime. The proposed distributed clustering algorithm is contrasted with the existing clustering algorithm LEACH.
... Sensor nodes send their sensed information to the CH during their respective TDMA time-slots. The CH performs data aggregation process and forwards the aggregated data to base station (BS) [3][4][5][6][7][8][9][10]. Clustering follows some advantages like network scalability, localizing route setup within the cluster, uses communication bandwidth efficiently and makes best use of network lifetime. ...
A wireless sensor network is used as an effective tool for gathering data in various situations. Recent researches in wireless communications and electronics has enforced the development of low-cost wireless sensor network. Wireless sensor networks are web of sensor nodes with a set of processors and limited memory unit embedded in it. Reliable routing of packets from sensor nodes to its base station is the most important function for these networks. The conventional routing protocols cannot be applied here due to its battery powered nodes. To support energy efficiency, nodes are often clustered in to non-overlapping clusters. This paper gives a brief overview on clustering process in wireless sensor networks. A research on the well evaluated distributed clustering algorithm Low Energy Adaptive Clustering Hierarchy (LEACH) and its followers are portrayed artistically. To overcome the drawbacks of these existing algorithms a distributed clustering model has been proposed for attaining energy efficiency to a larger scale.
... Few nodes may be gone without being part of any cluster, thereby no guarantee that every node takes part in clustering mechanism. Yu, Li and Levy [5] proposed DECA, which selects CH based on residual energy, connectivity and a unique node identifier. It is greatly energy efficient, as it uses fewer messages for CH selection. ...
Each sensor node has a microprocessor and a petite amount of memory. Also every sensor node is equipped with one or more sensing devices such as acoustic sensors, microphone arrays, video cameras, infrared, seismic or magnetic sensors. But it is difficult to replace the deceased batteries of the sensor nodes. A distinctive sensor node consumes much of its energy during wireless communication. This research work suggests the development of a hierarchical distributed clustering mechanism, which gives improved performance over the existing clustering algorithm LEACH. The two hiding concepts behind the proposed scheme are the hierarchical distributed clustering mechanism and the concept of threshold. Energy utilization is significantly reduced, thereby greatly prolonging the lifetime of the sensor nodes. Index Terms: Wireless sensor network, sensor node, cluster head, base station, residual energy, energy utilization, network lifetime.
... The power consumption by the sensors should be optimal to extend the life of the sensors. The sensor nodes can be equipped to internally process the information and broadcast only the requisite information thereby saving on network bandwidth([5],[10],[15]). Instead of centralized algorithms, localized algorithms are the key for the optimal use of the sensor network[12]. ...
... Normally, 1 nJ energy is required by a sensor processor to compute an instruction whereas Bluetooth transceiver is required about 100 nJ for single bit transmission. It can easily show that, for transmitting data packet of 1 KB over 100 m distance consumes about equal energy to compute three million instructions [8]. That is why, in the proposed scheme, we have focused on developing a new communication protocol to make the cluster based WSN more energy efficient. ...
Wireless sensor network will get wide applicability and acceptance if improved energy efficient routing protocol is implemented. Most of the cluster based hierarchical routing protocols use base station (BS) as a main controller to select cluster heads (CHs) which increases energy consumption and round trip time delay. In this paper, we propose an improved energy efficient routing protocol to maximize the network life time and reduce data delay time. In this proposed protocol, new CH is selected by the current CH instead of the BS based on the maximum residual energy and minimum distance between the CH and a node among all the nodes in a cluster. Unlike the modified LEACH (MLEACH), in the proposed protocol re-clustering is occurred only when the residual energy of the current CHs lower than a threshold value. From the comparison of the simulation results it is proved that the proposed protocol provides lower cluster formation time and network failure with better network fault tolerance and packet delivery ratio than the MLEACH.
... Obviously, the power breakdown heavily depends on the specific node, and the following remarks generally hold [87]: • The communication subsystem has an energy consumption much higher than the computation subsystem. G. Pottie [88] shown that transmitting one bit may consume as much as executing a few thousands instructions. Therefore, communication should be traded for computation. ...
The growth of wireless networks has resulted in part from requirements for connecting people and advances in radio technologies. Recently there has been an increasing trend towards enabling the Internet-of-Things (IoT). Thousands of tiny devices interacting with their environments are being inter-networked and made accessible through the Internet. For that purpose, several com- munications protocols have been defined making use of the IEEE 802.15.4 Physical and MAC layers. The 6LoWPAN Network Layer adaptation protocol is an example which bridges the gap between low power devices and the IP world. Since its release, the design of routing protocols became increasingly important and the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) emerged as the IETF proposed standard protocol for IPv6-based multi-hop Wireless Sensor Networks (WSN).
This thesis considers that the sensor nodes form a large IPv6 network making use of above technologies and protocols, and that the sensor nodes are enabled to run one or more applications. It is also assumed that the applications and the sensor nodes to which they are associated, are not always active, alternating between active and inactive states.
The thesis aims to design a new energy efficient communications solution for WSN by exploring the hypothesis that the network is aware of the traffic generated by the applications running in the sensor nodes. Therefore, the thesis provides two major contributions: 1) a cross- layer mechanism using application layer and network layer information to constrain RPL-defined routing trees (RPL-BMARQ); 2) an Application-Driven WSN node synchronization mechanism for RPL-BMARQ.
RPL-BMARQ is designed as an extension to the RPL routing protocol using information shared by the application and routing layers to construct Directed Acyclic Graphs (DAGs), allowing the nodes to select parents with respect to the applications they run. By jointly considering the neighbors of each node, the applications each node runs, and the forwarding capabilities of a node, we provide a communications solution which enables the data of every application and sensor node to be transferred, while keeping the overall energy consumed low by reducing the time the nodes are active and reducing the total number of multicast packets exchanged. Therefore, RPL-BMARQ helps reducing the network energy consumption since it restricts radio communication activities while maintaining throughput fairness and packet reception ratio high. The mechanism was evaluated using four scenarios with different network topologies and compared against "standard RPL". The results obtained show that the mechanism enables lower energy consumption since the nodes are more often put a sleep, reducing the total number of packets exchanged, while maintaining fairness and query success rates hight.
The Application-Driven WSN node synchronization mechanism for RPL-BMARQ was de- signed to maintain the sensor nodes synchronized according to the duty cycle of the applications they run. The mechanism jointly uses cross-layer information and the Exponentially Weighted Moving Average (EWMA) technique for calculating in run-time average network delays which are used to control the time the sensor nodes would sleep in the next cycle in order to wakeup just before the next activity period starts. This mechanism enables all the sensor nodes to go asleep and to wakeup in synchronism. The mechanism was theoretically evaluated and simulated, and the results obtained show that the synchronization mechanism works as previewed. The results also showed that, when designing WSN applications with this mechanism, the nodes not involved in communications are kept sleeping as much as possible, waking up when necessary and in synchronism.
In order to confirm the validity of the mechanisms designed, we also tested them in real environments where the results were confirmed.
... The core idea of S-MAC [4] is periodic listen and sleep in each node. Each node will keep a schedule of periodic listen and sleep, and it tries to get synchronized with its neighbors. ...
This paper presents medium access control (MAC) protocol designed for embedded sensor networks. I start with a protocol called MACAW, RTS-CTS-DS-DATA data packet exchange. Then I analyze the properties of some MAC protocols, including S-MAC, B-MAC and IEEE 802.15.4. According to the understanding of S-MAC, some advantages are summarized, such as energy saving, latency reduction, etc. however, there are still some disadvantages, including data packet lost, unfairness, synchronization. And then the similarities and differences between them are discussed. S-MAC is a novel technique to reduce energy consumption, but B-MAC is more efficient with long preamble. Using long preamble, B-MAC achieves collision avoidance and high channel utilization rate. B-MAC can minimize idle listening, but it needs bi-directional communication. Finally, the paper presents B-MAC design process and implementation result on MSP430.
... These issues concerned all major aspects of our civilization, beginning with human and social-religious sciences through biology, Internet and energy sources. Among these ideas were cheap intelligent devices equipped with multiple sensors, scattered over a given area, thus creating a network of interconnected detectors allowing the monitoring of various parameters of the natural environment, technological processes (industrial automation, robotics, construction materials analysis, etc.), residential houses (temperature, humidity, carbon dioxide, etc.) or population clusters (e.g., the road traffic intensity measurement) [2][3][4][5][6]. While being intelligent and cheap (and therefore easily swappable), such networks can be installed in/on the ground, in the air, under water, inside/on the human body, and in vehicles and buildings. ...
The importance of constructing wide-area sensor networks for holistic environmental state evaluation has been demonstrated. A general structure of such a network has been presented with distinction of three segments: local (based on ZigBee, Ethernet and ModBus techniques), core (base on cellular technologies) and the storage/application. The implementation of these techniques requires knowledge of their technical limitations and electromagnetic compatibility issues. The former refer to ZigBee performance degradation in multi-hop transmission, whereas the latter are associated with the common electromagnetic spectrum sharing with other existing technologies or with undesired radiated emissions generated by the radio modules of the sensor network. In many cases, it is also necessary to provide a measurement station with autonomous energy source, such as solar. As stems from measurements of the energetic efficiency of these sources, one should apply them with care and perform detailed power budget since their real performance may turn out to be far from expected. This, in turn, may negatively affect—in particular—the operation of chemical sensors implemented in the network as they often require additional heating.
... Energy is an extremely crucial resource because it not only determines the sensor nodes lifetime, but the network lifetime as well [3]. In WSNs, communication has been recognized as the ajor source of energy consumption and costs significantly more than computation [3][4]. Consequently, most of the existing routing techniques in WSN attempt to find the shortest path to the sink to minimize energy consumption. ...
Energy is an extremely crucial resource for Wireless Sensor Networks (WSNs). Many routing techniques have been proposed for finding the minimum energy routing paths with a view to extend the network lifetime. However, this might lead to unbalanced distribution of energy among sensor nodes resulting in, energy hole problem. Therefore, designing energy-balanced routing technique is a challenge area of research in WSN. Moreover, dynamic and harsh environments pose great challenges in the reliability of WSN. To achieve reliable wireless communication within WSN, it is essential to have reliable routing protocol. Furthermore, due to the limited memory resources of sensor nodes, full utilization of such resources with less buffer overflow remains as a one of main consideration when designing a routing protocol for WSN. Consequently, this paper proposes a routing scheme that uses SWARM intelligence to achieve both minimum energy consumption and balanced energy consumption among sensor nodes for WSN lifetime extension. In addition, data reliability is considered in our model where, the sensed data can reach the sink node in a more reliable way. Finally, buffer space is considered to reduce the packet loss and energy consumption due to the retransmission of the same packets. Through simulation, the performance of proposed algorithm is compared with the previous work such as EBRP, ACO, TADR, SEB, and CLR-Routing.
... Among them it is worth mentioning the work carried out by some European industrial groups such as IDA [Kaplan, 2001] and OSEK, that are devoted to integrate fieldbus technologies for Web/Internet and automotive software standards for embedded controls respectively. Another interesting area of research is the wireless fieldbus technology, not only in the fast moving sector of automotive industry where ITS (Intelligent Transportation Systems) programs are known worldwide, but also throughout every industrial sector [Pottie and Kaiser, 2000]. ...
In this paper it is presented the state-of-the-art in fieldbus technology, according with the authors’ particular experience, giving diverse points of view about the necessary skills for using development tools and involved electronic devices, currently present in the training market. Given its growing impact all over automotive industry, an introduction about the CAN fieldbus is presented, along with the software and hardware tools that configure training environments for this protocol. Following the two different CAN nodes developed currently by the authors, using the aforementioned tools, are presented. Finally, future developments with great potential in the education of engineers, and fieldbus training applied to automotive industry and others, are also mentioned.
... REPLICA ANALYSES FOR MMV SETTINGS Section II discussed two MMV settings. Both settings have applications in real-world problems such as magnetic resonance imaging [4, 5] and sensor networks [10]. Although numerous algorithms for MMV signal estimation have been proposed [12][13][14][19][20][21][22], what is missing is an information theoretic analysis of the best possible mean squared error (MSE) performance. ...
Compressed sensing (CS) demonstrates that sparse signals can be estimated from under-determined linear systems. Distributed CS (DCS) is an area of CS that further reduces the number of measurements by considering joint sparsity within signal ensembles. DCS with jointly sparse signals has applications in multi-sensor acoustic sensing, magnetic resonance imaging with multiple coils, remote sensing, and array signal processing. Multi-measurement vector (MMV) problems consider the estimation of jointly sparse signals under the DCS framework. Two related MMV settings are studied. In the first setting, each signal vector is measured by a different independent and identically distributed (i.i.d.) measurement matrix, while in the second setting, all signal vectors are measured by the same i.i.d. matrix. Replica analysis is performed for these two MMV settings, and the minimum mean squared error (MMSE), which turns out to be identical for both settings, is obtained as a function of the noise variance and number of measurements. Multiple performance regions for MMV are identified where the MMSE behaves differently as a function of the noise variance and the number of measurements. Belief propagation (BP) is a CS signal estimation framework that often achieves the MMSE asymptotically. A phase transition for BP is identified. This phase transition, verified by numerical results, separates the regions where BP achieves the MMSE and where it is suboptimal. Numerical results also illustrate that more signal vectors in the jointly sparse signal ensemble lead to a better phase transition. To showcase the application of MMV models, the MMSE of complex CS problems with both real and complex measurement matrices is analyzed.
... Such distributed nature offers opportunities for understanding patterns of interconnections as complex networks. Examples include the World Wide Web [119, 120], and distributed wireless sensor systems [121, 122]. The challenges are to control and optimise the dynamics of those systems, even in the absence of a central director. ...
The increasing power of computer technology does not dispense with the need to extract meaningful information out of data sets of ever growing size, and indeed typically exacerbates the complexity of this task. To tackle this general problem, two methods have emerged, at chronologically different times, that are now commonly used in the scientific community: data mining and complex network theory. Not only do complex network analysis and data mining share the same general goal, that of extracting information from complex systems to ultimately create a new compact quantifiable representation, but they also often address similar problems too. In the face of that, a surprisingly low number of researchers turn out to resort to both methodologies. One may then be tempted to conclude that these two fields are either largely redundant or totally antithetic. The starting point of this review is that this state of affairs should be put down to contingent rather than conceptual differences, and that these two fields can in fact advantageously be used in a synergistic manner. An overview of both fields is first provided, some fundamental concepts of which are illustrated. A variety of contexts in which complex network theory and data mining have be used in a synergistic manner are then presented. Contexts in which the appropriate integration of complex networks metrics can lead to improved classification rates with respect to classical data mining algorithms and, conversely, contexts in which data mining can be used to tackle important issues in complex network theory applications are illustrated. Finally, ways to achieve a tighter integration between complex networks and data mining, and open lines of research are discussed.
... When compared to LEACH protocol PEGASIS protocol is establish to save more energy and is more vigorous in node failure. Muruganathan et al. [7] developed a protocol that creates clusters of the similar size and uses multi-hop routing between cluster head and the base station. The cluster head forward the last hop is selected randomly from the sets of cluster heads to diminish the consignment of cluster head which are located nearest to the base station. ...
The wireless sensor network (WSN) is one of the budding exploring areas and fast rising fields in wireless communications. The sensor nodes in the network are generally small-size, low-cost, low-power and multi-function capabilities. Wireless sensor networks (WSNs) are used for various applications ; since numerous sensor nodes are usually deployed on remote and inaccessible places, the employment and preservation should be easy and scalable. Sensor nodes in the field being run out of energy quickly has been an issue and many energy efficient routing protocols have been proposed to solve this problem and preserve the long life of the network. This paper work proposes a hierarchical based node activation routing technique which shows energy efficiency. This technique selects cluster head with highest residual energy in each communication round of transmission to the base station from the cluster heads. Hierarchical based node activation routing technique with different levels of hierarchy simulation results prolongs the lifetime of the network compared to other clustering schemes and communication rounds of simulation increase significantly.
... Referring to [14], the transmission the energy and the reception energy can be defined as follows: ...
... Given that energy consumption is greatly influenced by particular hardware implementations, we provide relative energy consumption outcomes. As a guideline we follow previus accepted procedures [4], [35], i.e.: 1) Reception usually has an energy cost an order of magnitude lower than to Transmission, as Reception does not change transmitting power and, 2) Transmission has an energy cost two orders of magnitude higher than Process, due to the low energy efficiency of RF power amplifiers. These differences can increase up to three orders of magnitude for specific hardware. ...
Energy efficiency has been a leading issue inWireless Sensor Networks (WSNs) and has produced a vast amount of research. Although the classic tradeoff has been between quality of gathered data versus lifetime of the network, most works gave preference to an increased network lifetime at the expense of the data quality. A common approach for energy efficiency is partitioning the network into clusters with correlated data, where representative nodes simply transmit or average measurements inside the cluster. In this work, we explore the joint use of innetwork processing techniques and clustering algorithms. This approach seeks both high data quality with a controlled number of transmissions using an aggregation function and an energy efficient network partition, respectively. The aim of this combination is to increase energy efficiency without sacrificing the data quality. We compare the performance of the Second-Order Data-Coupled Clustering (SODCC) and Compressive-Projections Principal Component Analysis (CPPCA) algorithm combination, in terms of both energy consumption and quality of the data reconstruction, to other combinations of state of the art clustering algorithms and in-network processing techniques. Among all the considered cases, the SODCC+CPPCA combination revealed a perfect balance between data quality, energy expenditure and ease of network management. The main conclusion of this paper is that the design of WSN algorithms must be processing-oriented rather than transmission-oriented, i.e., investing energy on both clustering and in-network processing algorithms ensures both energy efficiency and data quality.
Wireless sensor networks (WSNs) are a special type of ad hoc network that can be used in areas where wiring and power supply are difficult, in areas that are inaccessible (for example, because of environmental pollution or war), and in temporary situations (such as when natural disasters occur or fixed communication networks are blocked). They do not require fixed network support and can be rapidly deployed; they have strong invulnerability and can be widely used in military, industrial, transportation, environmental protection, and other fields. Compared with conventional wireless networks, WSNs have severe node energy constraints, and energy exhaustion is the main determinant of WSN performance and the network operation cycle. Many factors affect the energy consumption of nodes, the most important of which is the routing algorithm. However, sensor networks have unique characteristics, and the routing algorithms used in earlier ad hoc networks cannot be applied in them. Therefore, it is necessary to design energy-saving routing algorithms for WSNs.
In this study the analysis of the influence and development of Supply Chain Management
(SCM) in Misurata Textile Factory (MTF) firm in Libya is presented. Some parameters such as
Leadership, Supplier supply management, Vision and plan statement, Evaluation, Process control
and Improvement, and Customer Focus, are analysed to establish if the current implementation
of SCM systems on MTF is well organized. Based on the interview discussion with top
management and middle managers of the firm, the findings indicate that the communication and
knowledge transfer between the workers are limited, top management empowerment has not yet
been implemented, the computerized information system does not exist due to its pursuit of
immediate profits and short-term benefits. As a conclusion, current SCM implementation
practices are not applied to the factory as the full package of the SCM implementation model.
Therefore the firm could identify which areas urgently need improvement by using this model.
To maximize community lifetime in Wireless Sensor Networks (WSNs) the paths for statistics switch are decided
on in the sort of way that the entire electricity fed on alongside the direction is minimized. To guide high scalability
and better information aggregation, sensor nodes are frequently grouped into disjoint, non overlapping subsets
known as clusters. Clusters create hierarchical WSNs which contain green utilization of constrained sources of
sensor nodes and accordingly extends network lifetime. The goal of this paper is to provide a kingdom of the art
survey on clustering algorithms stated within the literature of WSNs. Our paper affords a taxonomy of power
efficient clustering algorithms in WSNs. And also gift timeline and description of LEACH and Its descendant in
WSNs.
Wireless sensor networks (WSN) are inheriting many application areas like environment observation, target tracking, border monitoring and battle field surveillance. To alleviate the problem of energy utilization and extending the lifetime of wireless sensor nodes, one approach is employing an effective clustering mechanism. In this paper variable power energy efficient clustering (VEEC) mechanism for wireless sensor networks has been proposed. It is a well distributed, energy efficient clustering algorithm which employs relay nodes, variable transmission power and single message transmission per node for setting up the cluster. The proposed scheme is compared with two existing distributed clustering algorithms LEACH and HEED. Simulation results clearly show an excellent improvement in average communication energy and the total energy of the wireless sensor system. Simulation study also shows the reduction in node death rate and prolongation in network lifetime compared to the two existing algorithms.
Wireless Sensor Networks (WSNs) has gained tremendous popularity in various practical applications, in which sensors are fundamentally battery-powered and significantly resource-limited. Well-designed Medium Access Control (MAC) protocols can make great contribution on the performance of the networks. In this paper, we present a survey on some typical or newly proposed MAC protocols which aims at enhancing energy efficiency of the networks. The classification and beneficial characteristics of MAC protocols are discussed. Furthermore, we analyze the protocols’ performance in various fields, and point out the open research issue.
Convergence of MEMS (Micro Electronic Mechanical System), digital electronics and wireless communication have increased the feasibility of WSN (Wireless Sensor Networks). This paper explains the basic concept of wireless sensor networks and explains the sensing function and important applications of sensor network applications. The factors affecting the development of sensor networks are also discussed. The survey provides communication architecture for sensor networks and techniques used for every layer.
Spatially distributed sensors, which communicate wirelessly form a wireless sensor network (WSN). This network monitors physical or environmental conditions. A central gateway, called high energy communication node, collects data from all sensors and sends them to the central computer where they are processed. We need to minimize the number of sensors and energy consumption of the network, when the terrain is fully covered. We convert the problem from multi-objective to mono-objective. The new objective function is a linear combination between the number of sensors and network energy. We propose ant colony optimization (ACO) algorithm to solve the problem. We compare our results with the state of the art in the literature.
Global dissemination of information and tools for computer networks, has allowed for major system attacks affecting critical network points and resulting in significant network performance degradation. In this paper, we present a probabilistic modelling framework for the propagation of an energy-constrained mobile threat in a wireless ad hoc network. The motivation behind this approach can be found in the topology-constrained character of the ad hoc setting, its dynamic nature and the stochastic characteristics of the interactions among the involved events. The introduced formulation is used to identify and evaluate different attack strategies and approaches. Through modelling and simulation, we evaluate the impact of various parameters associated with the operational characteristics of the mobile attacker on an outbreak spreading and the network evolution. Furthermore, a new metric, which indicates the overall infection-capability of each attack strategy is proposed and used to characterise the potential of each strategy to harm the network.
Wireless Sensor Networks, are made of low-cost, low
-power, small in
size, and multifunctional sensor
nodes. The efficient energy utilization is one of t
he important performance factors for wireless senso
r
networks survivability be-cause nodes operate with
limited battery power. In this paper we propose and
analyze a new approach of zone based clustering hea
d selection algorithm for wireless sensor network o
f
homogeneous nodes. Nodes in the network are uniform
ly distributed. In this clustering algorithm, netwo
rk
performance is improved by selecting cluster heads
on the basis of the residual energy of existing clu
ster
heads, and nearest hop distance of the node. In thi
s paper we evaluate various performance metrics lik
e
energy consumption, network life time, number of ch
annel heads metrics in each round and compare these
with respect to random algorithm i.e. LEACH. We con
clude that proposed protocol effectively extends th
e
network lifetime without degrading the other critic
al overheads and perform-ance metrics.
The lifetime of battery operated wireless sensor networks can be prolonged by energy aware maintenance of the virtual backbone. The energy of a node is depleted quickly during communication and network failure is most likely to occur when the energy of a Minimum Connected Dominating Set (MCDS) node is exhausted. The reconstruction of an alternate backbone without the depleted node is both time and energy intensive. In the present study, local repair technique based on neighborhood information has been proposed and evaluated for extending lifetime. An energy depleted node is deleted and the backbone is repaired with other nodes to allow communication. It has been shown that the number of such extra nodes required for repairing the backbone is limited to five. Simulation results shows that the network lifetime extends significantly especially in large dense networks when the local repair is adopted as compared to networks without repair.
In recent years most of the research in the field of sensor networks is allocated to the wireless sensor and actor networks due to their complicacy and vastness of research area. This type of network is a group of sensors and actors wirelessly linked to each other. Sensors gather information of physical world while actors take appropriate decisions on the basis of gathered information and then perform proper actions upon the environment. In wireless sensor and actor networks, it is very important to maintain the connection between actors. Failure of one or more actors can break up the network into separated parts and this failure acts as a barrier to the network to perform its duties. The purpose of the present paper was to provide a genetic algorithm in wireless sensor and actor networks, to improve evaluation and to maintain the connection between actors’ networks. In order to evaluate strong points and weaknesses of the recommended approach, the OMNet++ simulation was used and the outcomes of the simulation were indicative of the recommended approach’s validity.
A wireless sensor network can be particularly vulnerable to security attacks lacking physical boundaries to the environment. In contrast with conventional networks, wireless sensor networks has constrained energy reserves, so data encryption in sensor networks should consume as little energy as possible. In this paper, we propose a light-weight stream cipher using fundamental arithmetic instructions. Compared to existing public or symmetric key based schemes, our proposed method is considerably more energy-friendly.
Because of nodes mobility, one of important and fundamental issues in mobile sensor networks is how to cluster the nodes in network. The clustering is a method for best managing nodes energies, data collectting and sending information to base station and increasing network lifetime. In a wireless mobile network, the created clusters change continually and the nodes move from one cluster to another, constantly. Therefore, using fault tolerant methods capable to creating new clusters while the moving of nodes between clusters, will be necessary. One of clustering methods in mobile Ad-Hoc networks is based on neighborhood benchmark in which, the cluster heads are selected based on maximum connection degree and minimum fault in a specific time period. In this paper, the improvement of mentioned method in term of increasing network lifetime, based on its combination with minimum hop number to cluster head, will be considered. With using this new method, having symmetric and balanced-sized clusters with cluster heads that have most communications and least faults, will be possible.
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