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Sensor networks provide applications in many diverse areas. This is for the simple fact that they are reliable, flexible, easily deployable and highly cost-effective. Smart sensors can provide such diverse services as detecting signs of machine failures, sensing earthquakes, onset of flooding and even provide a warning system for potential terrorist attacks. Because the sensors are untethered and battery powered, these networks have to maintain a high yield to the energy spent per sensor device. These yields translate into mainly throughputs and packet latencies while keeping the energy usage at the minimum. In this work, we look at the communication level energy usage within the sensor networks and propose novel scheme for channel access optimized for energy consumption and rate control algorithms for traffic engineering and congestion control in wireless sensor networks. The first involves a novel medium access protocol for wireless sensor networks. The protocol is based on exploiting the periodicity inherent in carrier sensing schemes like CSMA/CA combined with a relaxed time-access arbitration regime among the competing nodes. Transmission and reception of data frames are made to be strictly receiver triggered events which makes it possible to bring down idle-listening drastically. The protocol also provides a way to make the channel access collision-free among the two-degree neighbors. PMAC requires no additional control signaling and no network-wide synchronization. The protocol does not seek to make any tradeoff for the gains in energy efficiency with latency or throughput. It presents high-energy efficiency and throughput improvement in low as well as high-traffic scenarios of sleeping. In the second part, we propose novel rate-control algorithms for the wireless sensor networks. There has been a growth in personal area network technologies like Bluetooth etc to support various applications that require multimedia level QoS in a high interference environment. Applications such as voice data traffic, file transfers, periodic synching of electronic devices within the range of 10m-15m requires sophisticated yet simple channel access techniques that accommodate different QoS requirements of these applications. In this context, the new rate control algorithms were designed that reduces the interference and maximized the throughput and reliability parameters such as packet success rates, packet latency and aggregate throughput per flow. Moreover, the rate control algorithm also takes into account the fairness issues among the competing flows in terms of the bandwidth-share.
Wireless Sensor Networks have a wide range of applications in different areas. Their main constraint is the limited and irreplaceable power source of the sensor nodes. In many applications, energy conservation of the sensor nodes and their replacement or replenishment due to the hostile nature of the environment is the most challenging issue. Energy efficient clustering and routing are the two main important topics studied extensively for this purpose. This book focuses on the energy efficient clustering and routing with a great emphasis on the evolutionary approaches. It provides a comprehensive and systematic introduction of the fundamentals of WSNs, major issues and effective solutions.
The advances in low-power electronic devices integrated with wireless communication capabilities are one of recent areas of research in the field of Wireless Sensor Networks (WSNs). One of the major challenges in WSNs is uniform and least energy dissipation while increasing the lifetime of the network. This is the first book that introduces the energy efficient wireless sensor network techniques and protocols. The text covers the theoretical as well as the practical requirements to conduct and trigger new experiments and project ideas. The advanced techniques will help in industrial problem solving for energy-hungry wireless sensor network applications.
Wireless Sensor Networks have a wide range of applications in different areas. Their main constraint is the limited and irreplaceable power source of the sensor nodes. In many applications, energy conservation of the sensor nodes and their replacement or replenishment due to the hostile nature of the environment is the most challenging issue. Energy efficient clustering and routing are the two main important topics studied extensively for this purpose. This book focuses on the energy efficient clustering and routing with a great emphasis on the evolutionary approaches. It provides a comprehensive and systematic introduction of the fundamentals of WSNs, major issues and effective solutions.
This book constitutes the refereed proceedings of the 9th International Conference on Distributed Computing and Internet Technology, ICDCIT 2013, held in Bhubaneswar, India, in February 2013. The 40 full papers presented together with 5 invited talks in this volume were carefully reviewed and selected from 164 submissions. The papers cover various research aspects in distributed computing, internet technology, computer networks, and machine learning.
Wireless networking covers a variety of topics involving many challenges. The main concern of clustering approaches for mobile wireless sensor networks (WSNs) is to prolong the battery life of the individual sensors and the network lifetime. For a successful clustering approach, the need of a powerful mechanism to safely elect a cluster head remains a challenging task in many research works that take into account the mobility of the network. In Mobile, Wireless and Sensor Networks: A Clustering Algorithm for Energy Efficiency and Safety, the authors use an approach based on computing of the weight of each node in the network as the proposed technique to deal with this problem. They present a virtual laboratory platform (VLP) of baptized mercury, allowing students and researchers to make practical work (PW) on different aspects of mobile wireless sensor networks. The authors’ choice of WSNs is motivated mainly by the use of real experiments needed in most college courses on WSNs. These usual experiments, however, require an expensive investment and many nodes in the classroom. The platform presented here aims at showing the feasibility, the flexibility, and the reduced cost using the authors’ approach. The authors demonstrate the performance of the proposed algorithms that contribute to the familiarization of the learners in the field of WSNs. The book will be a valuable resource for students in networking studies as well as for faculty and researchers in this area.
Master's Thesis from the year 2013 in the subject Computer Science - Internet, New Technologies, grade: 8.12, , course: M. Tech, language: English, abstract: Wireless sensor network (WSN) is an emerging imperious leading technology of the current century that presents great promise for various pioneering applications. The use of sensor networks should keep developing, mainly in the fields of scientific, logistic, healthcare and military applications. Sensor networks interact and collect sensitive data and operate in unattended hostile environments, thus it is imperative to pay attention to the security of wireless sensor networks as they are highly prone to threats. For successful operation of the nodes, it is important to maintain the security and privacy of the transmitted data as well as the data stored at nodes. The different security protocols and models used in the wired and other wireless networks such as ad-hoc networks cannot be used in WSNs because the sensor size poses significant restrictions, mainly in terms of energy autonomy and node lifetime, as the batteries have to be too tiny. Also, the existing security protocols in these constrained networks are not sufficiently energy efficient, which is the real motivation behind this work. In this thesis, a light-weight dynamic security algorithm titled “An Energy Efficient and Dynamic Security Protocol (EEDSP)” for wireless sensor networks has been proposed and implemented at nodal level. We also implement an existing algorithm and then carry out the performance analysis of both the algorithms in terms of energy consumptions, node lifetime and memory requirements at source and intermediate nodes to verify the improvement in our protocol’s results.
With the rapid growth of technology in society, communication networks have become a heavily researched topic. Implementing these advanced systems is a challenge, however, due to the abundance of optimization problems within these networks. The use of meta-heuristic algorithms and nature-inspired computing has become a prevalent technique among researchers for solving these complex problems within communication networks. Despite its popularity, this specific computing technique lacks the appropriate amount of research that is needed for professionals to grasp a definite understanding. Nature-Inspired Computing Applications in Advanced Communication Networks is a collection of innovative research on the methods and applications of natural computation techniques and algorithms within communication systems such as wireless sensor networks, vehicular adhoc networks, and internet of things. While highlighting topics including mobile sensor deployment, routing optimization, and sleep scheduling, this book is ideally designed for researchers, network professionals, computer scientists, mathematicians, developers, scholars, educators, and students seeking to enhance their understanding of nature-inspired computing and its solutions within various advanced communication networks.
This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intelligence and working on these topics.