IEEE 802.11 rate adaptation: a practical approach
MSWiM '04 Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
Proceedings of the 10th annual international conference on Mobile computing and networking
Near-optimal sensor placements: maximizing information while minimizing communication cost
Proceedings of the 5th international conference on Information processing in sensor networks
Deploying wireless sensors to achieve both coverage and connectivity
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Deployment analysis in underwater acoustic wireless sensor networks
WUWNet '06 Proceedings of the 1st ACM international workshop on Underwater networks
Movement-assisted sensor redeployment scheme for network lifetime increase
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
Distributed virtual-movement scheme for improving energy efficiency in wireless sensor networks
Proceedings of the 12th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
Rapidly-deployable mesh network testbed
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
The rapidly deployable radio network
IEEE Journal on Selected Areas in Communications
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In this paper, we propose an algorithm to efficiently (re)-deploy the wireless mobile routers of a substitution network by considering the energy consumption, a fast deployment scheme and a mix of the network metric. We consider a scenario where we have two routers in a fixed network and where a robust connection must be restored between those two routers with a wireless mobile router. The main objective of the wireless mobile router is to increase the communication performance such as the throughput by acting as relay node between the two routers of the fixed network. We present a fast, adaptive and localized approach which takes into account different network metrics such as Received Signal Strength (RSS), Round-Trip Time (RTT) and the Transmission Rate, between the wireless mobile router and the two routers of the fixed network. Our method ameliorates the performance of our previous approach from the literature by shortening the deployment time, increasing the throughput, and consuming less energy in some specific cases.