Energy Efficiency in Wireless Sensor Network: A Review

In wireless sensor networks (WSNs) improving the lifetime of is directly related to the energy efficiency of computation and communication operations in the sensor nodes. Compressive sensing (CS) theory suggests a new way of sensing the signal with a much lower number of linear measurements as compared to the conventional case provided that the underlying signal is sparse. This result has implications on WSN energy efficiency and prolonging network lifetime. In this paper, the effects of acquiring, processing, and communicating CS-based measurements on WSN lifetime are analyzed in comparison to conventional approaches. the energy dissipation characteristics of WSNs utilizing the concepts of compressive sensing is investigated and compared to two other well known conventional approaches (DANP and DATC). Our results show that compressive sensing prolongs network lifetime significantly in comparison to conventional approaches provided that the acquired signals are highly sparse (e.g., K/N ≤ 0.10) and node density in the network is not too low (e.g., Rnet ≤ 150 m and ζ = 50). Keywords— Compressive sensing (CS), energy efficiency, mixed integer programming, network lifetime, wireless sensor networks (WSN