Dynamic Wireless Sensor Networks

Author: Sharief M. A. Oteafy
Publisher: John Wiley & Sons
ISBN: 111876207X
Size: 57.33 MB
Format: PDF
View: 3536

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Dynamic Wireless Sensor Networks. In this title, the authors leap into a novel paradigm of scalability and cost-effectiveness, on the basis of resource reuse. In a world with much abundance of wirelessly accessible devices, WSN deployments should capitalize on the resources already available in the region of deployment, and only augment it with the components required to meet new application requirements. However, if the required resources already exist in that region, WSN deployment converges to an assignment and scheduling scheme to accommodate for the new application given the existing resources. Such resources are polled from many fields, including multiple WSNs already in the field, static networks (WiFi, WiMAX, cellular, etc) in addition to municipal, industrial and mobile resources.The architecture, framework and pricing policy, as well as approaches for backward compatibility with existing deployments, are presented in this book. We elaborate on the formalization of the problem, and contrast with existing work on coverage. This paradigm adopts optimal assignments in WSNs and exploits dynamic re-programming for boosting post-deployment and backward compatible protocols.

Dynamic Wireless Sensor Networks

Author: Sharief M. A. Oteafy
Publisher: John Wiley & Sons
ISBN: 1848215312
Size: 43.38 MB
Format: PDF, Docs
View: 7476

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Dynamic Wireless Sensor Networks. Subject to tremendous redesign and development in the last decade, wireless sensor networks are advanced and highly in demand, but continue to fall short of their widely perceived potential. This text addresses attempts to scale wireless sensor networks to larger regions and augment their functionality. It insists that the networks can improve their levels of scalability and cost effectiveness while capitalizing on the already existing, reusable technologies available to our disposal. Written for system architects, designers, manufacturers, and students, this book includes information on the architecture, framework, and pricing policy in addition to suggesting sustainable solutions for development

Dynamic Wireless Sensor Networks

Author: Sharief M. A. Oteafy
Publisher: John Wiley & Sons
ISBN: 1118762045
Size: 78.99 MB
Format: PDF, ePub, Mobi
View: 191

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Dynamic Wireless Sensor Networks. In this title, the authors leap into a novel paradigm of scalability and cost-effectiveness, on the basis of resource reuse. In a world with much abundance of wirelessly accessible devices, WSN deployments should capitalize on the resources already available in the region of deployment, and only augment it with the components required to meet new application requirements. However, if the required resources already exist in that region, WSN deployment converges to an assignment and scheduling scheme to accommodate for the new application given the existing resources. Such resources are polled from many fields, including multiple WSNs already in the field, static networks (WiFi, WiMAX, cellular, etc) in addition to municipal, industrial and mobile resources.The architecture, framework and pricing policy, as well as approaches for backward compatibility with existing deployments, are presented in this book. We elaborate on the formalization of the problem, and contrast with existing work on coverage. This paradigm adopts optimal assignments in WSNs and exploits dynamic re-programming for boosting post-deployment and backward compatible protocols.

Wireless Sensor Networks

Author: Jorge Sá Silva
Publisher: Springer Science & Business Media
ISBN: 3642119166
Size: 65.54 MB
Format: PDF
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Wireless Sensor Networks. This book constitutes the refereed proceedings of the 7th European Conference on Wireless Sensor Networks, EWSN 2010, held in Coimbra, Portugal, in Februar 2010. The 21 revised full papers presented were carefully reviewed and selected from 109 submissions. Topics of interest include hardware design and implementation, operating systems and software, middleware and macroprogramming, communication and network protocols, information and signal processing, fundamental theoretical limits and algorithms, prototypes, field experiments, testbeds, novel applications, including urban sensing, security and fault-tolerance. The papers are organized in topical sections on localization, synchronization and compression, networking, new directions, programming and architecture, as well as on link reliability.

Dynamic Target Classification In Wireless Sensor Networks

Author: Ying Sun
Publisher:
ISBN:
Size: 38.21 MB
Format: PDF
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Dynamic Target Classification In Wireless Sensor Networks. Information exploitation schemes with high-accuracy and low computational cost play an important role in Wireless Sensor Networks (WSNs). This thesis studies the problem of target classification in WSNs. Specifically, due to the resource constraints and dynamic nature of WSNs, we focus on the design of the energy-effcient solution with high accuracy for target classification in WSNs. Feature extraction and classification are two intertwined components in pattern recognition. Our hypothesis is that for each type of target, there exists an optimal set of features in conjunction with a specific classifier, which can yield the best performance in terms of classification accuracy using least amount of computation, measured by the number of features used. Our objective is to find such an optimal combination of features and classifiers. Our study is in the context of applications deployed in a wireless sensor network (WSN) environment, composed of large number of small-size sensors with their own processing, sensing and networking capabilities powered by onboard battery supply. Due to the extremely limited resources on each sensor platform, the decision making is prune to fault, making sensor fusion a necessity. We present a concept, referred to as dynamic target classification in WSNs. The main idea is to dynamically select the optimal combination of features and classifiers based on the "probability" that the target to be classified might belong to a certain category. We use two data sets to validate our hypothesis and derive the optimal combination sets by minimizing a cost function. We apply the proposed algorithm to a scenario of collaborative target classifi- cation among a group of sensors which are selected using information based sensor selection rule in WSNs. Experimental results show that our approach can significantly reduce the computational time while at the same time, achieve better classification accuracy without using any fusion algorithm, compared with traditional classification approaches, making it a viable solution in practice.