NETWORK LIFETIME MAXIMIZATION BASED ON ENERGY FORECAST AND COMPRESSIVE SENSING WITH INTEGRATED SINK MOBILITY FOR HETEROGENOUS WIRELESS SENSOR NETWORKS

摘要

Optimum usage of battery resources and efficient consumption of energy are the primary concerns and design parameters for any WSN. Irregular energy consumption is the major problem in current WSNs. This paper focuses on efficiently using the energy resources and to maximize the network lifetime by the application of compressive sensing and optimum CH selection process coupled with sink mobility model. Compressive sensing allows us to reduce the number of transmissions taken for complete data transfer, while optimum CH election mechanism gives efficient energy consumption at the initial stages of transmissions and data transfer. The residual energy of the network is further optimized by using the sink mobility model, increasing the total lifetime of high energy nodes thereby leading to increased network lifetime. The algorithm was simulated in MATLAB and verified.