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Architecture and protocols for the Internet of Things: A case study
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In this paper, we describe a practical realization of an Internet-of-Things (IoT) architecture at the University of Padova, Italy. Our network spans the floors of different buildings within the Department of Information Engineering, and is designed to provide access to basic services such as environmental monitoring and localization to University users, as well as to manage service access based on user roles and authorizations. The network is based on a flexible and expandable infrastructure allowing easy node management. A support for the 6LoWPAN standard makes nodes reachable from outside the network using IPv6 and provides an infrastructure to realize IoT applications.
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... Smart campus was originally a development of a digital campus, by integrating all service applications to create a better academic environment [8] [9]. Smart campuses are generally built based on IoT (Internet of Things) technology, Big Data, artificial intelligence, and computer networks [10], [11], [12]. ...
... By understanding technology as an extension of human tools, from the simplest to the most complex, we can see how spirituality and technology alike stem from the human need for transcendence and the search for meaning. Coeckelbergh [9] and Szerszynski [10] further illustrate this symbiotic relationship through conceptual metaphors that highlight similarities between spirituality and technology. Therefore, incorporating smart spirituality into university education not only enriches the theoretical understanding of intellectual actors but also connects them to the deeper and universal dimensions of humanity. ...
... Our proposed protocol employs a dynamic buffer occupancy to detect congestion, as well as a modified AIMD algorithm to mitigate network congestion. In their study, [35] introduced three distinct congestion control strategies, namely griping, deaf, and fuse. Our proposal, referred to as OHCA, regulates the flow of unidirectional and bidirectional traffic on CoAP/6LoWPAN networks. ...
The Internet of Things (IoT) consists of non-standardized computer devices that can create wireless network connections to send data. These devices have limited storage, bandwidth, and computing capacities, which may cause network congestion when nodes move or leave their allotted area. IoT networks need congestion control to enhance the efficiency of data transfer. The study examines IoT congestion and proposes using alternate nodes to maintain dataflow and quality of service (QoS). The study presents RAoNC, a novel algorithm designed to improve routing algorithms in network clusters for the purposes of congestion monitoring, avoidance, and mitigation. Congestion management techniques efficiently process network information update query packets and reduce large-header handshaking packets. Improve network performance by reducing congestion, packet loss, and throughput. The proposed method speeds up packet transfer to reduce network node packet transmission delays. The optimization approach minimizes power usage across all network nodes. We assessed the efficacy of our approach by comparative analysis utilizing NS2 simulations and contrasted the suggested algorithm with prior studies. The simulation shows that RAoNC significantly improves congestion performance. We will assess the novel RAoNC algorithm in relation to DCCC6, LEACH, and QU-RPL. The throughput increased by 28.36%, weighted fairness index by 28.2%, end-to-end delay by 48.7%, energy consumption by 31.97%, and the number of missed packets in the buffer decreased by 90.35%.
... In their study, [55] presented three unique congestion control strategies: gripping, deaf, and fuse. The purpose of these systems is to control the movement of traffic, both in one direction and in two directions, over CoAP/6LoWPAN networks. ...
The main challenge for IoT-enabled networks lies in the transmission of large volumes of data produced by sensor nodes. The overconsumption of communication power presents a risk to the longevity of nodes. Hence, it is imperative to offer remedies for network-related problems such as Quality of Service (QoS), security, network heterogeneity, congestion avoidance, reliable routing, and energy conservation. Routing protocols are crucial for addressing the aforementioned issues of sending data across different firms. Data aggregation techniques are essential for the collection and consolidation of information in order to reduce traffic congestion , operational costs, energy consumption, and the lifespan of the network. Developing reliable, energy-efficient, and efficient route planning is challenging in scenarios where data is aggregated for Internet of Things (IoT) applications. The current investigation presents a novel routing system named Cluster-based Energy-aware & Nearest Neighbour Protocol (CEnNP), which utilizes NS2 simulation. The technique use decision trees and neural networks to evaluate the probability of a successful delivery. When training the model, we consider various factors such as the predictability value obtained from the CEnNP routing scheme, node popularity, node power consumption, speed, and location. The simulation findings indicate that CEnNP outperforms a reliable routing system for NS2 1 in terms of successful deliveries, lost messages, overhead, and hop count. However , these enhancements result in only marginal increments in buffer length and buffer occupancy levels. The proposed hybrid routing technique consists of two main stages: cluster formation and intra-and inter-cluster routing. The findings indicate that CEnNP outperforms prior studies in terms of network resilience, packet transmission efficiency, end-to-end delay, and energy consumption
... Objects use this technology to identify other objects so that they can connect to each other. This technology also detects objects in real time and provides important information such as location and status (Castellani et al., 2010). IoT is enabled by a robust RFID system. ...
The study aimed to find out the readiness and the competence of academic staff in tertiary institutions to use the Internet of Things in instruction delivery process, as well as to identify the acceptance of students in tertiary institutions to use this technology in the teaching and learning process. A sample size of fifty (50) academic staff and sixty (60) students was used for the study. In the course of this study, the researcher used a self-made questionnaire. The statistical method used in data analysis in this research was the simple mean. A mean value of 2.50 and above on a scale of 5.00 was set as high enough to affirm a particular question in the questionnaire, whereas mean values of less than 2.50 was seen as not enough to affirm such question. The importance of this research lies in the fact that it afforded a background and firsthand information on acceptability and the nature of Internet of things (IoT) that can be implemented in tertiary institutions, in addition to providing decision makers responsible for the educational process with basic information related to the effectiveness of the use of modern technology in education, then developing the educational process in line with modern technologies, and the requirements of the modern era. This study came out with a set of results, the most important of which are that academic staff and students have positive motivations for using internet of things in educational process. The study further recommended that in addition to providing internet of things devices in academic institutions, regular training is a necessity to ensure a complete integration of modern technology in to the teaching and learning process in tertiary institutions.
Through sensors the modern living is made much easier and comfortable in many ways. The perfect blend of sensors and actuators create Internet of Things (IOT) through which the information is shared across the devices in normal day to day life. Combined with RFID (Radio Frequency Identifiers) the IoT has emerged as a Future Internet. Internet of Things means connecting Machine to Machine, Machine to Infrastructure, Machine to Environment and much more Internet of Everything. It can be done using embedded systems and many useful actions that can command and control can be made to make our lives easier and safer. This paper studies various aspects of the Internet of Things in detail.
Current IoT systems are characterized by using resource-constrained electronic devices therefore new lightweight protocols should be designed to reduce communications costs, computational costs, and storage costs. For such requirements many researchers have already proposed various novel methodologies here we have analysed all of these. This research paper includes a survey of lightweight approaches for IoT protocols.
The web is the most powerful paradigm on the Internet today. The widespread use of web services, almost universally in enterprise and Internet services, makes them very attractive for use in sensor networks as well. With the rapid expansion of IPv6 in sensor networks thanks to the 6LoWPAN standard, it is possible to implement web services suitable for very embedded nodes and networks. The SENSEI project makes use of web service concepts and a resource model to realize the SENSEI framework for the embedded web. This paper introduces Binary Web Services (BinaryWS), which enables end-to-end web services for even the most constrained devices and networks. Also, the paper analyzes several key schemes for encoding XML, which greatly reduce payload sizes. Results are given for the implementation of BinaryWS on Contiki and TinyOS sensor nodes, and for the comparison of XML encoding schemes for typical sensor network XML payloads. Results from an early experimental campaign proven the scalability of the approach. The combination of the BinaryWS protocol and the Efficient XML Interchange (EXI) standard are shown to be ideal for realizing the embedded web.
In the last couple of years, huge research effort has been spent focusing on the realization of wireless sensor networks, especially in the area of radio interface effi-ciency, power consumption, ad-hoc networking, routing etc. In this paper we would like to focus on how sensors/ actuators and sensor networks can be integrated into the Internet and therefore supporting the development of IP-based applications in different domains. The work, which will be introduced in the following, represents intermediate results of a joint R&D project between Samsung Advanced Institute of Technology and Fraunhofer FOKUS. The main outcome of the project is a Home Services Framework with respective functions and protocols, based on a middleware layer that integrates different sensor networking technologies, home automa-tion technologies and consumer electronics into the Inter-net.
Today's buildings account for a large fraction of our en-ergy consumption. In an effort to economize scarce fossil fu-els on earth, sensor networks are a valuable tool to increase the energy efficiency of buildings without severely reducing our quality of life. Within a smart building many sensors and actuators are interconnected to form a control system. Nowa-days, the deployment of a building control system is compli-cated because of different communication standards. In this paper, we present a web services-based approach to integrate resource constrained sensor and actuator nodes into IP-based networks. A key feature of our approach is its capability for automatic service discovery. For this purpose, we imple-mented an API to access services on sensor nodes follow-ing the architectural style of representational state transfer (REST). We implemented a prototype application based on TinyOS 2.1 on a custom sensor node platform with 8 Kbytes of RAM and an IEEE 802.15.4 compliant radio transceiver.
This paper presents SYNAPSE++, a system for over the air reprogramming of wireless sensor networks (WSNs). In contrast to previous solutions, which implement plain negative acknowledgment-based ARQ strategies, SYNAPSE++ adopts a more sophisticated error recovery approach exploiting rateless fountain codes (FCs). This allows it to scale considerably better in dense networks and to better cope with noisy environments. In order to speed up the decoding process and decrease its computational complexity, we engineered the FC encoding distribution through an original genetic optimization approach. Furthermore, novel channel access and pipelining techniques have been jointly designed so as to fully exploit the benefits of fountain codes, mitigate the hidden terminal problem and reduce the number of collisions. All of this makes it possible for SYNAPSE++ to recover data over multiple hops through overhearing by limiting, as much as possible, the number of explicit retransmissions. We finally created new bootloader and memory management modules so that SYNAPSE++ could disseminate and load program images written using any language. At the end of this paper, the effectiveness of SYNAPSE++ is demonstrated through experimental results over actual multihop deployments, and its performance is compared with that of Deluge, the de facto standard protocol for code dissemination in WSNs. The TinyOS 2 code of SYNAPSE++ is available at http://dgt.dei.unipd.it/download.
This paper gives a detailed technical overview of some of the activities carried out in the context of the "Wireless Sensor networks for city-Wide Ambient Intelligence (WISE-WAI)" project, funded by the Cassa di Risparmio di Padova e Rovigo Foundation, Italy. The main aim of the project is to demonstrate the feasibility of large-scale wireless sensor network deployments, whereby tiny objects integrating one or more environmental sensors (humidity, temperature, light intensity), a microcontroller and a wireless transceiver are deployed over a large area, which in this case involves the buildings of the Department of Information Engineering at the University of Padova. We will describe how the network is organized to provide full-scale automated functions, and which services and applications it is configured to provide. These applications include long-term environmental monitoring, alarm event detection and propagation, single-sensor interrogation, localization and tracking of objects, assisted navigation, as well as fast data dissemination services to be used, e.g., to rapidly re-program all sensors over-the-air. The organization of such a large testbed requires notable efforts in terms of communication protocols and strategies, whose design must pursue scalability, energy efficiency (while sensors are connected through USB cables for logging and debugging purposes, most of them will be battery-operated), as well as the capability to support applications with diverse requirements. These efforts, the description of a subset of the results obtained so far, and of the final objectives to be met are the scope of the present paper.
We present a web service based approach to enable an evolutionary sensornet system where additional sensor nodes may be added af- ter the initial deployment. The functionality and data provided by the new nodes is exposed in a structured manner, so that multiple applications may access them. The result is a highly inter-operable system where multiple applications can share a common evolving sensor substrate. A key challenge in using web services on resource constrained sensor nodes is the energy and bandwidth overhead of the structured data formats used in web services. Our work pro- vides a detailed evaluation of the overheads and presents an imple- mentation on a representative sensor platform with 48k of ROM, 10k of RAM and a 802.15.4 radio. We identify design choices that optimize the web service operation on resource constrained sen- sor nodes, including support for low latency messaging and sleep modes, quantifying trade-offs between the design generality and re- source efficiency. We also prototyped an example application, for home energy management, demonstrating how evolutionary sensor networks can be supported with our approach.
Smart object networks and their applications give rise to challenges both at the node and the network level. To meet these challenges a network architecture is required that is interoperable across a wide range of communication technologies, that evolves as the field of smart objects evolves, and that is scalable enough to meet the challenges imposed by large-scale smart object networks while lightweight enough for the node-level resource constraints. This chapter focuses on how IP architecture meets these goals while providing unprecedented interoperability with existing networks, applications, and services. Interoperability is a predominant characteristic of the IP architecture. It is interoperable because it runs over link layers with very different characteristics, providing interoperability among them and because IP provides interoperability with existing networks, applications, and protocols. Standardization plays a large part in the success of IP's interoperability. IP is standardized by an established standardization organization that provides mechanisms through which new standards are reviewed and vetted. This process puts a large amount of effort into ensuring that the mechanisms and protocols proposed as standards can be efficiently implemented. From the outset, the IP architecture was designed to allow application layer protocols and mechanisms to evolve independently of the underlying network protocols and mechanisms. The IP architecture has also been thoroughly field-proven regarding scalability through the use of IP over the public Internet.
"It is stunningly thorough and takes readers meticulously through the design, con?guration and operation of IPv6-based, low-power, potentially mobile radio-based networking." Vint Cerf, Vice President and Chief Internet Evangelist, Google This book provides a complete overview of IPv6 over Low Power Wireless Area Network (6LoWPAN) technology In this book, the authors provide an overview of the 6LoWPAN family of standards, architecture, and related wireless and Internet technology. Starting with an overview of the IPv6 'Internet of Things', readers are offered an insight into how these technologies fit together into a complete architecture. The 6LoWPAN format and related standards are then covered in detail. In addition, the authors discuss the building and operation of 6LoWPAN networks, including bootstrapping, routing, security, Internet ingration, mobility and application protocols. Furthermore, implementation aspects of 6LoWPAN are covered. Key Features: Demonstrates how the 6LoWPAN standard makes the latest Internet protocols available to even the most minimal embedded devices over low-rate wireless networks Provides an overview of the 6LoWPAN standard, architecture and related wireless and Internet technology, and explains the 6LoWPAN protocol format in detail Details operational topics such as bootstrapping, routing, security, Internet integration, mobility and application protocols Written by expert authors with vast experience in the field (industrial and academic) Includes an accompanying website containing tutorial slides, course material and open-source code with examples (http://6lowpan.net ) 6LoWPAN: The Wireless Embedded Internet is an invaluable reference for professionals working in fields such as telecommunications, control, and embedded systems. Advanced students and teachers in electrical engineering, information technology and computer science will also find this book useful.
Sensor networks are seen as an important part in emerging office and building energy management system, but the integration of sensor networks with future energy management systems is still an open problem. We present an IP-based sensor network system where nodes communicate their information using Web services, allowing direct integration in modern IT systems. Our system uses two mechanisms to provide a good performance and low-power operation: a session-aware power-saving radio protocol and the use of the HTTP Conditional GET mechanism. We perform an extensive evaluation of our system and show that Web services are a viable mechanism for use in low-power sensor networks. Our results show that Web service requests can be completed well below one second and with a low power consumption, even in a multi-hop setting.