PROJECT TITLE :

ESP: Evaluation-Based Skeleton Pruning in Sensor Networks

ABSTRACT:

Skeleton has been successfully incorporated in the design of high-performance protocol in sensor networks. As there exists a tradeoff between skeleton simplicity and reconstruction error, it's necessary to quantitatively judge the skeleton and refine it properly. While some studies on skeleton extraction and refinement are proposed, there still lacks deep understanding of quantitative evaluation and skeleton pruning. In this paper, we contemplate each the simplicity and reconstruction ability of skeleton, and present ESP, an evaluation-primarily based skeleton pruning algorithm. By analyzing the skeleton properties, we first present the adjusted coverage index of skeleton to measure its goodness, and then offer a completely unique approach for skeleton pruning. We additionally analyze that the adjusted coverage index is closely connected to the performance of skeleton-based mostly applications, and show by simulations that the ESP can properly decide the skeleton’s goodness and yield a refined skeleton.