DocumentCode
1725367
Title
Resource management in Visual Sensor Networks using Nash Bargaining Solution in generalized fading
Author
Odejide, O.O. ; Bentley, E.S. ; Kondi, Lisimachos P. ; Matyjas, John D.
Author_Institution
Air Force Res. Lab., Rome, NY, USA
fYear
2013
Firstpage
283
Lastpage
287
Abstract
In this paper we consider the problem of resource management for a Direct Sequence Code Division Multiple Access (DS-CDMA) wireless Visual Sensor Network (VSN) in a generalized fading environment. In a VSN application, the primary goal is ensuring that maximum video quality is achieved in spite of the prevailing network resource constraints. The Nash Bargaining Solution (NBS) was used in determining the transmission power and source and channel coding rates for each node. The nodes in the network negotiate in order to determine their transmission parameters. The task is to optimize the transmission powers (which are continuous) and the source and channel coding rates (which are discrete) for all the network nodes. Particle Swarm Optimization (PSO) is used to solve the mixed-integer optimization that arises. The analysis was carried out for a myriad of wireless multipath fading environments using a unified moment generating function (MGF) approach.
Keywords
channel coding; code division multiple access; fading channels; game theory; integer programming; multipath channels; particle swarm optimisation; radiofrequency power transmission; resource allocation; source coding; video communication; wireless sensor networks; DS-CDMA VSN; NBS; Nash bargaining solution; PSO; channel coding rates; direct sequence code division multiple access wireless visual sensor network; generalized fading; maximum video quality; mixed-integer optimization; network resource constraints; particle swarm optimization; power transmission; resource management; source coding rates; transmission parameters; unified MGF approach; unified moment generating function approach; visual sensor networks; wireless multipath fading environments; Channel coding; Fading; Optimization; Resource management; Visualization; Wireless communication; Wireless sensor networks; Nash bargaining solution; cross layer optimization; game theory; moment generating function; multipath fading; particle swarm optimization; visual sensor network;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Communications and Networking Conference (CCNC), 2013 IEEE
Conference_Location
Las Vegas, NV
Print_ISBN
978-1-4673-3131-9
Type
conf
DOI
10.1109/CCNC.2013.6488459
Filename
6488459
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