  In this paper, we combat the problem of performance optimization in wireless
sensor networks. Specifically, a novel framework is proposed to handle two
major research issues. Firstly, we optimize the utilization of resources
available to various nodes at hand. This is achieved via proposed optimal
network clustering enriched with layer-adaptive 3-tier communication mechanism
to diminish energy holes. We also introduce a mathematical coverage model that
helps us minimize the number of coverage holes. Secondly, we present a novel
approach to recover the corrupted version of the data received over noisy
wireless channels. A robust sparse-domain based recovery method equipped with
specially developed averaging filter is used to take care of the unwanted noisy
components added to the data samples. Our proposed framework provides a handy
routing protocol that enjoys improved computation complexity and elongated
network lifetime as demonstrated with the help of extensive simulation results.
