Hybridizing Biogeography-Based Optimization With Differential Evolution for Optimal Power Allocation in Wireless Sensor Networks

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...

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Veröffentlicht in:IEEE transactions on vehicular technology Jg. 60; H. 5; S. 2347 - 2353
Hauptverfasser: Boussaid, I, Chatterjee, A, Siarry, P, Ahmed-Nacer, M
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.06.2011
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Allocations
Applied sciences
Biogeography-based optimization (BBO) algorithm
Computer Science
Constraints
Covariance matrix
Detection, estimation, filtering, equalization, prediction
differential evolution (DE) algorithm
Error probability
Evolution
Exact sciences and technology
Information, signal and communications theory
Networks
Noise
Operations Research
optimal power allocation
Optimization
Optimization algorithms
Receivers
Resource management
Sensors
Services and terminals of telecommunications
Signal and communications theory
Signal, noise
Stochasticity
Studies
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Telemetry. Remote supervision. Telewarning. Remote control
wireless sensor network (WSN)
Wireless sensor networks
Performance evaluation
differential evolution (DE) algorithm
Error probability
Evolutionary algorithm
Wireless telecommunication
Numerical method
Biogeography-based optimization (BBO) algorithm
Deterministic signal
Stochastic method
Power allocation
Optimization
Remote sensing
Case study
Optimal allocation
wireless sensor network (WSN)
Wireless network
Optimal planning
Sensor array
Signal detection
Comparative study
optimal power allocation
ISSN:0018-9545, 1939-9359
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Beschreibung
Zusammenfassung: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.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2011.2151215