Information Processing And Routing In Wireless Sensor Networks

This book presents state-of-the-art cross-layer optimization techniques for energy-efficient information processing and routing in wireless sensor networks. Besides providing a survey on this important research area, three specific topics are discussed in detail OCo information processing in a collocated cluster, information transport over a tree substrate, and information routing for computationally intensive applications. The book covers several important system knobs for cross-layer optimization, including voltage scaling, rate adaptation, and tunable compression. By exploring tradeoffs of energy versus latency and computation versus communication using these knobs, significant energy conservation is achieved. Sample Chapter(s). Chapter 1: Introduction to Wireless Sensor Networks (421 KB). Contents: Introduction of Wireless Sensor Networks; Background; Energy Models; Information Processing within a Collocated Cluster; Information Transportation over a Tree Substrate; Information Routing with Tunable Compression. Readership: Researchers and graduate students in networking and electrical engineering."

Publisher Description

This book presents state-of-the-art cross-layer optimization techniques for energy-efficient information processing and routing in wireless sensor networks. Besides providing a survey on this important research area, three specific topics are discussed in detail ? information processing in a collocated cluster, information transport over a tree substrate, and information routing for computationally intensive applications. The book covers several important system knobs for cross-layer optimization, including voltage scaling, rate adaptation, and tunable compression. By exploring tradeoffs of energy versus latency and computation versus communication using these knobs, significant energy conservation is achieved.

This book constitutes the refereed proceedings of the Second International Workshop on Information Processing in Sensor Networks, IPSN 2003, held in Palo Alto, CA, USA, in April 2003. The 23 revised full papers and 21 revised poster papers presented were carefully reviewed and selected from 73 submissions. Among the topics addressed are wireless sensor networks, query processing, decentralized sensor platforms, distributed databases, distributed group management, sensor network design, collaborative signal processing, adhoc sensor networks, distributed algorithms, distributed sensor network control, sensor network resource management, data service middleware, random sensor networks, mobile agents, target tracking, sensor network protocols, large scale sensor networks, and multicast.

Overview and Goals Wireless communication technologies are undergoing rapid advancements. The last few years have experienced a steep growth in research in the area of wireless sensor networks (WSNs). In WSNs, communication takes place with the help of spatially distributedautonomoussensornodesequippedtosensespeci?cinformation. WSNs, especially the ones that have gained much popularity in the recent years, are, ty- cally, ad hoc in nature and they inherit many characteristics/features of wireless ad hoc networks such as the ability for infrastructure-less setup, minimal or no reliance on network planning, and the ability of the nodes to self-organize and self-con?gure without the involvement of a centralized network manager, router, access point, or a switch. These features help to set up WSNs fast in situations where there is no existing network setup or in times when setting up a ?xed infrastructure network is considered infeasible, for example, in times of emergency or during relief - erations. WSNs ?nd a variety of applications in both the military and the civilian population worldwide such as in cases of enemy intrusion in the battle?eld, object tracking, habitat monitoring, patient monitoring, ?re detection, and so on. Even though sensor networks have emerged to be attractive and they hold great promises for our future, there are several challenges that need to be addressed. Some of the well-known challenges are attributed to issues relating to coverage and deployment, scalability, quality-of-service, size, computational power, energy ef?ciency, and security.

Wireless sensor networks (WSNs) are a valuable technology to support a huge range of applications spanning from military to commercial, such as battlefield surveillance, habitat monitoring, forest fire detection, disaster salvage, and inventory control management. It has the capability to reveal previously unobservable phenomena in the physical world and significant flexibility of installation and manipulation. The major challenges of WSNs design come from the requirements of energy constraint, distributed control and scalability. In this thesis we studied three topics on WSNs. The first one was energy-efficient medium access control (MAC) protocol design. We proposed a MAC protocol which schedules the send and receive times for all nodes within the network. As all nodes only wake up when they send or receive, significant energy is saved by reducing idle listening, collisions and overhearing. And we evaluated the protocol performance by using the GloMoSim simulator. The second topic was about distributed transmission power control of wireless sensor nodes. We proposed a simple scheme which employs request-to-send (RTS) and clear-to-send (CTS) frames to exchange channel gain information, based on which concurrent senders determine their own transmission power without a central controller to coordinate them. Simulation results showed that our scheme can save 30% to 50% of the energy, and also reduce transmissionlatency. The third topic was on event detection. Due to the fact that wireless sensor nodes are spatially distributed throughout the area of interest, this application has to been implemented in distributed form. We proposed a scheme which does not need a pre-designated fusion node, and this greatly improves network scalability. We provided close-form expressions to estimate the probabilities of detection failure and false alarm, and validated them by extensive simulation.

A wireless sensor network (WSN) uses a number of autonomous devices to cooperatively monitor physical or environmental conditions via a wireless network. Since its military beginnings as a means of battlefield surveillance, practical use of this technology has extended to a range of civilian applications including environmental monitoring, natural disaster prediction and relief, health monitoring and fire detection. Technological advancements, coupled with lowering costs, suggest that wireless sensor networks will have a significant impact on 21st century life. The design of wireless sensor networks requires consideration for several disciplines such as distributed signal processing, communications and cross-layer design. Wireless Sensor Networks: Signal Processing and Communications focuses on the theoretical aspects of wireless sensor networks and offers readers signal processing and communication perspectives on the design of large-scale networks. It explains state-of-the-art design theories and techniques to readers and places emphasis on the fundamental properties of large-scale sensor networks. Wireless Sensor Networks: Signal Processing and Communications : Approaches WSNs from a new angle – distributed signal processing, communication algorithms and novel cross-layer design paradigms. Applies ideas and illustrations from classical theory to an emerging field of WSN applications. Presents important analytical tools for use in the design of application-specific WSNs. Wireless Sensor Networks will be of use to signal processing and communications researchers and practitioners in applying classical theory to network design. It identifies research directions for senior undergraduate and graduate students and offers a rich bibliography for further reading and investigation.

With classical techniques for data transmission soon reaching their limitations, cognitive approaches may offer a solution to user requirements for better coverage, connectivity, security, and energy efficiency at lower cost. Wireless Sensor Networks: A Cognitive Perspective presents a unified view of the state of the art of cognitive approaches in telecommunications. A benchmark in the field, it brings together research that has previously been scattered throughout conference and journal papers. Cutting-Edge Topics in Cognitive Communications After a review of the cognitive concept and approaches, the book outlines a generic architecture for cognition in wireless sensor networks. It then targets specific issues that need to be addressed through cognition, from cognitive radio and spectrum access to routing protocols. The book also explores how to use weighted cognitive maps to improve network lifetime through optimizing routing, medium access, and power control while fulfilling end-to-end goals. The final chapter discusses the implementation of hardware for GPS/INS-enabled wireless sensor networks. This addresses an important need for real-time node position information in many wireless sensor network applications and communication protocols. Real-World Applications of Wireless Sensor Networks using the Cognitive Concept Written in a tutorial style, the book supplies an in-depth survey of each topic, accompanied by detailed descriptions of the algorithms and protocols. It also provides a step-by-step analysis of the various communications systems through extensive computer simulations and illustrations. Examples cover environmental monitoring, vehicular communications, tracking, and more. A comprehensive overview of cognitive communications in wireless sensor networks, this work lays the foundations for readers to participate in a new era of research in this emerging field.

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.