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Three applications in wireless networks where model-free stochastic learning is applicable, are discussed. The learning based optimization problems are formulated and simulation results are presented. Some open issues are also discussed.
This paper presents a distributed fermat-point range estimation strategy, which is important in the moving sensor localization applications. The fermat-point is defined as a point which minimizes the sum of distances from three sensors inside a triangle. This point is indeed at the trianglepsilas center of gravity. We solve the problems of large errors and poor performance in the bounding box algorithm...
In this paper, we propose an adaptive pacing scheme at the link layer for IEEE 802.11 based multihop wireless networks. Our objective is to improve the performance of higher layer protocols without any modifications to them. Our adaptive pacing scheme estimates the four-hop transmission delay in the network path without incurring any additional overheads, and accordingly paces the packets to reduce...
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