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.

Meeting Name

12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016 (2016: May 26-28, Washington, DC)


Computer Science

Research Center/Lab(s)

Intelligent Systems Center


This work has been partially supported by the Academy of Finland under grant number 284806 and by the US National Science Foundation under grants CNS-1355505, CNS1545050, CNS-1545037, CSR-1353111, and CCF-1351786.

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)


Document Type

Article - Conference proceedings

Document Version


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© 2016 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 May 2016