An efficient compressive data gathering routing scheme for large-scale wireless sensor networks

• An energy efficient sparse random projection clustering routing data gathering scheme is presented.
• The optimal cluster heads can be obtained based energy consumption model.
• The scheme guarantees all cluster heads uniformly distributed approximately.
• The scheme prolongs the network’s lifetime significantly via experiment comparisons.

Compressive sensing based in-network compression is an efficient technique to reduce communication cost and accurately recover sensory data at the sink. Existing compressive sensing based data gathering methods require a large number of sensors to participate in each measurement gathering, and it leads to waste a lot of energy. In this paper, we present an energy efficient clustering routing data gathering scheme for large-scale wireless sensor networks. The main challenges of our scheme are how to obtain the optimal number of clusters and how to keep all cluster heads uniformly distributed. To solve the above problems, we first formulate an energy consumption model to obtain the optimal number of clusters. Second, we design an efficient deterministic dynamic clustering scheme to guarantee all cluster heads uniformly distributed approximately. With extensive simulation, we demonstrate that our scheme not only prolongs nearly 2× network’s lifetime compared with the state of the art compressive sensing based data gathering schemes, but also makes the network energy consumption very uniformly.

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