Comparative Analysis on the Competitiveness of Conventional and Compressive Sensing-based Query Processing

Optimization of the lifetime of the battery within wireless sensor networks (WSNs) is challenging due to communication infrastructure. Subsequently, minimizing the amount of power required for data collection and processing to serve the intended purposes has become an open research problem. Conventional and compressive sensing-based (CS) query processing being the candidates to perform these tasks, require a comparative analysis in the current WSN application context. In this paper. Simulations have been carried out to compare the performance of conventional and compressive sensing-based (CS) query processing with respect to energy efficiency, sensing reliability and normalized estimation error within WSN. A significant reduction in the computational complexity reaching 70% is noticed using CS compared to conventional query processing algorithms. Moreover, it is observed that up to 90% sensing reliability can be achieved with CS compared to existing query processing. Hence, the reduction in computational complexity has not compromised the sensing reliability with an observed reduction in the normalized estimation error.

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