A distributed evolutionary algorithmic approach to the least-cost connected constrained sub-graph and power control problem

Jason C. Tillett; Raghuveer Rao; Ferat Sahin; T. M. Rao

doi:10.1117/12.541663

10 August 2004 A distributed evolutionary algorithmic approach to the least-cost connected constrained sub-graph and power control problem

Jason C. Tillett, Raghuveer Rao, Ferat Sahin, T. M. Rao

Author Affiliations +

Proceedings Volume 5440, Digital Wireless Communications VI; (2004) https://doi.org/10.1117/12.541663
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

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.

Citation Download Citation

Jason C. Tillett, Raghuveer Rao, Ferat Sahin, and 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); https://doi.org/10.1117/12.541663

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