Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/DCOSS.2016.14 | 2016 International Conference on Distributed Computing in Sensor Systems (DCOSS) |
Keywords | Field | DocType |
Wireless sensor networks,gene regulatory networks,bio-inspired,nanoscale properties,robustness,efficient communications,performance evaluation | Key distribution in wireless sensor networks,Computer science,Latency (engineering),Computer network,Robustness (computer science),Network topology,Mobile wireless sensor network,Gene regulatory network,Wireless sensor network,Energy consumption,Distributed computing | Conference |
ISSN | ISBN | Citations |
2325-2936 | 978-1-5090-1461-3 | 4 |
PageRank | References | Authors |
0.43 | 18 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Azade Nazi | 1 | 56 | 11.61 |
| Mayank Raj | 2 | 106 | 12.13 |
| Mario Di Francesco | 3 | 1573 | 69.29 |
| Preetam Ghosh | 4 | 349 | 43.69 |
| Sajal K. Das | 5 | 8086 | 745.54 |