Nature-Inspired Computing for Autonomic Wireless Sensor Networks
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InBook{Sarbazi-Azad:2014:lsncds,
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author = "Hamid Sarbazi-Azad and Albert Y. Zomaya",
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booktitle = "Large Scale Network-Centric Distributed Systems",
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title = "Nature-Inspired Computing for Autonomic Wireless
Sensor Networks",
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year = "2014",
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pages = "760-",
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DOI = "doi:10.1002/9781118640708.ch11",
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publisher = "Wiley-IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "9781118640708",
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URL = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6674272",
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abstract = "This chapter presents how nature-inspired algorithms
can affect the underlying design principles, enabling
technologies, implementation, and management issues of
autonomic wireless sensor networks (WSNs). It explains
how WSN can benefit from autonomic mechanisms. The
chapter provides a brief introduction to
nature-inspired computing. It reviews several current
nature-inspired techniques such as genetic algorithms
(GA) and genetic programming (GP) to construct
autonomic WSN. The chapter also presents the
state-of-the-art techniques in those areas. It
introduces several works such as bio-networking
architecture, and biologically-inspired architecture
for sensor NETworks (BiSNET) in which multiple
biological principles are used to build fundamental
frameworks for implementing autonomic WSNs.
Self-organized mechanisms alleviate the dependence of
sensors on a central controller and therefore help
sensors to consume energy more efficiently in reaching
the primary goal of WSNs to prolong their lifetime.",
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notes = "Also known as \cite{6674272}",
- }
Genetic Programming entries for
Hamid Sarbazi-Azad
Albert Y Zomaya
Citations