JOURNAL ARTICLE

Energy-efficient communication in wireless cable sensor networks

Xiao ChenN. C. Rowe

Year: 2012 Journal:   International Journal of Parallel Emergent and Distributed Systems Vol: 28 (4)Pages: 289-307   Publisher: Taylor & Francis

Abstract

In this paper, we introduce a new type of sensor: cable sensor. Unlike traditional point sensors, this type of sensor has a rectangular sensing region with a processor installed on it to do processing and communication. The wireless network formed by this kind of sensor is called wireless cable sensor network (WCSN). We study energy-efficient communication algorithms in WCSNs. We address it in two ways: one is through reducing the total transmission power of processors while maintaining the connectivity of the network and the other is through scheduling cable sensors to let them take turns to go to sleep without affecting the coverage and connectivity of the network. In the first approach, we initially develop a distributed algorithm called DTRNG based on the relative neighbourhood graph. Later we enhance it to Algorithm determine the transmission power by removing the largest edge in CYCles (DTCYC). Mathematical proofs show that Algorithm DTCYC provides an optimal solution that can not only minimise the total processor transmission power but maintain the connectivity of the network as well. In the second approach, we propose a cable mode transition algorithm which determines the minimum number of active sensors to maintain K-coverage as well as K-connectivity required by the application. We discuss the relationship between coverage and connectivity and prove the theorems that lay the foundation for our algorithm. Simulation results demonstrate that our algorithm is efficient in saving energy.

Keywords:
Wireless sensor network Computer science Sleep mode Key distribution in wireless sensor networks Efficient energy use Wireless Algorithm Brooks–Iyengar algorithm Scheduling (production processes) Transmission (telecommunications) Distributed algorithm Wireless network Distributed computing Computer network Real-time computing Power (physics) Engineering Electrical engineering Telecommunications Mathematics Mathematical optimization

Metrics

5
Cited By
0.00
FWCI (Field Weighted Citation Impact)
19
Refs
0.11
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Energy Efficient Wireless Sensor Networks
Physical Sciences →  Computer Science →  Computer Networks and Communications
Energy Harvesting in Wireless Networks
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications

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