Title :
Hybridizing Biogeography-Based Optimization With Differential Evolution for Optimal Power Allocation in Wireless Sensor Networks
Author :
Boussa?¯d, Ilhem ; Chatterjee, Amitava ; Siarry, Patrick ; Ahmed-Nacer, Mohamed
Author_Institution :
Univ. of Sci. & Technol., Algiers, Algeria
fDate :
6/1/2011 12:00:00 AM
Abstract :
This paper studies the performance of a wireless sensor network (WSN) in the context of binary detection of a deterministic signal. This paper aims to develop a numerical solution for the optimal power allocation scheme via a variation of the biogeography-based optimization (BBO) algorithm, which is called the constrained BBO-DE algorithm. This new stochastic optimization algorithm is a hybridization of a very recently proposed stochastic optimization algorithm, i.e., the BBO algorithm, with another popular stochastic optimization algorithm called the differential evolution (DE) algorithm. The objective is to minimize the total power spent by the whole sensor network under a desired performance criterion, which is specified as the detection error probability. The proposed algorithm has been tested for several case studies, and its performances are compared with those of two constrained versions of the BBO and DE algorithms.
Keywords :
error statistics; geography; optimisation; resource allocation; wireless sensor networks; binary detection; biogeography hybrid; differential evolution; error probability; numerical solution; optimal power allocation scheme; stochastic optimization algorithm; wireless sensor networks; Covariance matrix; Error probability; Noise; Optimization; Receivers; Resource management; Wireless sensor networks; Biogeography-based optimization (BBO) algorithm; differential evolution (DE) algorithm; optimal power allocation; wireless sensor network (WSN);
Journal_Title :
Vehicular Technology, IEEE Transactions on
Conference_Location :
5/5/2011 12:00:00 AM
DOI :
10.1109/TVT.2011.2151215