Combined bio-inspired/evolutionary computational methods in cross-layer protocol optimization for wireless ad hoc sensor networks

William S. Hortos

doi:10.1117/12.884818

19 May 2011 Combined bio-inspired/evolutionary computational methods in cross-layer protocol optimization for wireless ad hoc sensor networks

William S. Hortos

Author Affiliations +

Proceedings Volume 8059, Evolutionary and Bio-Inspired Computation: Theory and Applications V; 80590Q (2011) https://doi.org/10.1117/12.884818
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

Published studies have focused on the application of one bio-inspired or evolutionary computational method to the functions of a single protocol layer in a wireless ad hoc sensor network (WSN). For example, swarm intelligence in the form of ant colony optimization (ACO), has been repeatedly considered for the routing of data/information among nodes, a network-layer function, while genetic algorithms (GAs) have been used to select transmission frequencies and power levels, physical-layer functions. Similarly, artificial immune systems (AISs) as well as trust models of quantized data reputation have been invoked for detection of network intrusions that cause anomalies in data and information; these act on the application and presentation layers. Most recently, a self-organizing scheduling scheme inspired by frog-calling behavior for reliable data transmission in wireless sensor networks, termed anti-phase synchronization, has been applied to realize collision-free transmissions between neighboring nodes, a function of the MAC layer. In a novel departure from previous work, the cross-layer approach to WSN protocol design suggests applying more than one evolutionary computational method to the functions of the appropriate layers to improve the QoS performance of the cross-layer design beyond that of one method applied to a single layer's functions. A baseline WSN protocol design, embedding GAs, anti-phase synchronization, ACO, and a trust model based on quantized data reputation at the physical, MAC, network, and application layers, respectively, is constructed. Simulation results demonstrate the synergies among the bioinspired/ evolutionary methods of the proposed baseline design improve the overall QoS performance of networks over that of a single computational method.

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William S. Hortos "Combined bio-inspired/evolutionary computational methods in cross-layer protocol optimization for wireless ad hoc sensor networks", Proc. SPIE 8059, Evolutionary and Bio-Inspired Computation: Theory and Applications V, 80590Q (19 May 2011); https://doi.org/10.1117/12.884818

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KEYWORDS

Sensor networks

Sensors

Detection and tracking algorithms

Data modeling

Network security

Biomimetics

Computer intrusion detection

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