Description
When wireless sensors are capable of variable transmit power and are battery powered, it is important to select the appropriate transmit power level for the node. Lowering the transmit power of the sensor nodes imposes a natural clustering on the network and has been shown to improve throughput of the network. However, a common transmit power level is not appropriate for inhomogeneous networks. A possible fitness-based approach, motivated by an evolutionary optimization technique, Particle Swarm Optimization (PSO) is proposed and extended in a novel way to determine the appropriate transmit power of each sensor node. A distributed version of PSO is developed and explored using experimental fitness to achieve an approximation of least-cost connectivity.
Date of creation, presentation, or exhibit
8-10-2004
Document Type
Conference Paper
Department, Program, or Center
Microelectronic Engineering (KGCOE)
Recommended Citation
Jason C. Tillett, Raghuveer Rao, Ferat Sahin, T. M. Rao, "A distributed evolutionary algorithmic approach to the least-cost connected constrained sub-graph and power control problem", Proc. SPIE 5440, Digital Wireless Communications VI, (10 August 2004); doi: 10.1117/12.541663; https://doi.org/10.1117/12.541663
Campus
RIT – Main Campus
Comments
Copyright 2004 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.