Maximizing Energy Efficient Techniques in Wireless Sensor Networks: Algorithms for Maximizing Network Lifetime - Image 1

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LAP Lambert Academic Publishing Maximizing Energy Efficient Techniques in Wireless Sensor Networks: Algorithms for Maximizing Network Lifetime

Name: Maximizing Energy Efficient Techniques in Wireless Sensor Networks: Algorithms for Maximizing Network Lifetime
Brand: LAP Lambert Academic Publishing
Price: 54.0 GBP
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Network Topics

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Description

Recent advances in Wireless Communication and Embedded Microprocessors have led to the development of small, low cost sensor devices. A wireless Sensor Network consists of a large number of sensors distributed over a geographical area with their locations either previously fixed or randomly deployed. Energy consumption is the most important factor to determine the life of a sensor network. Sensor nodes are driven by a battery and have very low energy resources. We have achieved optimization of energy and maximizing the network life through Network Coverage, Optimal deployment of multiple base stations to overcome bottleneck in single base station and clustering scheme that is completely controlled by the base station, Optimal Scheduling, Solving Dead End problem results in high packet delivery ratio to the base station and Impact of mobility models on performance of routing protocol with respect to Packet Delivery Ratio, Latency and Throughput in wireless sensor networks. Energy Efficient Algorithms and Performance Analysis are useful for students and research community pursuing in the field of Wireless Sensor Networks, Ubiquitous and Pervasive Computing.

Product Specifications

Brand: LAP Lambert Academic Publishing
Format: paperback
ASIN: 365915072X
Category: Books > Subjects > Computing & Internet > Networking & Security > Network Topics
Domain: Amazon UK
Release Date: 09 August 2012
Listed Since: 13 August 2012

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LAP Lambert Academic Publishing Maximizing Energy Efficient Techniques in Wireless Sensor Networks: Algorithms for Maximizing Network Lifetime

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