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In this paper, we combat the problem of performance optimization in wirelesssensor networks. Specifically, a novel framework is proposed to handle twomajor research issues. Firstly, we optimize the utilization of resourcesavailable to various nodes at hand. This is achieved via proposed optimalnetwork clustering enriched with layer-adaptive 3-tier communication mechanismto diminish energy holes. We also introduce a mathematical coverage model thathelps us minimize the number of coverage holes. Secondly, we present a novelapproach to recover the corrupted version of the data received over noisywireless channels. A robust sparse-domain based recovery method equipped withspecially developed averaging filter is used to take care of the unwanted noisycomponents added to the data samples. Our proposed framework provides a handyrouting protocol that enjoys improved computation complexity and elongatednetwork lifetime as demonstrated with the help of extensive simulation results.

Layer-Adaptive Communication and Collaborative Transformed-Domain Representations for Performance Optimization in WSNs