STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Energy-efficient forwarding strategies for geographic routing in lossy wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Optimal Transmission Radius for Flooding in Large Scale Sensor Networks
Cluster Computing
Exploring Spatial Correlation for Link Quality Estimation in Wireless Sensor Networks
PERCOM '06 Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications
Energy-Efficient Forwarding Schemes for Wireless Sensor Networks
WOWMOM '06 Proceedings of the 2006 International Symposium on on World of Wireless, Mobile and Multimedia Networks
Statistical model of lossy links in wireless sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Models and solutions for radio irregularity in wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
Algorithmic construction of sets for k-restrictions
ACM Transactions on Algorithms (TALG)
An analysis of unreliability and asymmetry in low-power wireless links
ACM Transactions on Sensor Networks (TOSN)
Predicting link quality using supervised learning in wireless sensor networks
ACM SIGMOBILE Mobile Computing and Communications Review
Analysis of Forwarding Mechanisms on Fine-Grain Gradient Sinking Model in WSN
Journal of Signal Processing Systems
Hi-index | 0.00 |
Link quality is one of the most important factors that affect the performance of wireless networks. In a densely deployed wireless network, continuous link quality monitoring consumes significant amount of energy and bandwidth at each node. In this paper, we propose a sensitivity model and a spatial correlation model that can be used to derive a set of deputy links to monitor, instead of monitoring all of the links in the network. The proposed scheme can improve energy efficiency of the link quality monitoring process. A greedy algorithm is presented to derive the deputy links set based on three different optimization objective functions. Performance of the proposed method is studied extensively and it is shown that the proposed method can save almost 90% energy in typical simulation scenarios than the method of monitoring all links. We also demonstrate that the energy consumption of the greedy deputy set-based method is upper-bounded. Copyright © 2010 John Wiley & Sons, Ltd.