Efficient Communications in Wireless Sensor Networks based on Biological Robustness
Robustness in wireless sensor networks (WSNs) is a critical factor that largely depends on their network topology and on how devices can react to disruptions, including node and link failures. This article presents a novel solution to obtain robust WSNs by exploiting principles of biological robustness at nanoscale. Specifically, we consider Gene Regulatory Networks (GRNs) as a model for the interaction between genes in living organisms. GRNs have evolved over millions of years to provide robustness against adverse factors in cells and their environment. Based on this observation, we apply a method to build robust WSNs, called bio-inspired WSNs, by establishing a correspondence between the topology of GRNs and that of already-deployed WSNs. Through simulation in realistic conditions, we demonstrate that bio-inspired WSNs are more reliable than existing solutions for the design of robust WSNs. We also show that communications in bio-inspired WSNs have lower latency as well as lower energy consumption than the state of the art.
A. Nazi et al., "Efficient Communications in Wireless Sensor Networks based on Biological Robustness," Proceedings of the 12th Annual International Conference on Distributed Computing in Sensor Systems (2016, Washington, DC), pp. 161 - 168, Institute of Electrical and Electronics Engineers (IEEE), May 2016.
The definitive version is available at https://doi.org/10.1109/DCOSS.2016.14
12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016 (2016: May 26-28, Washington, DC)
Intelligent Systems Center
Keywords and Phrases
Biology; Computer network performance evaluation; Distributed computer systems; Energy utilization; Genes; Nanotechnology; Robustness (control systems); Sensor nodes; Topology; Bio-inspired; Efficient communications; Gene regulatory networks; Nanoscale properties; Performance evaluation; Wireless sensor networks
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
© 2016 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 May 2016