An Adaptive Mixed Algorithm for Lifetime Optimization in Dense Wireless Sensor Network

The problem of data collection in wireless sensor networks (WSNs) is becoming critical as larger networks are being deployed. Increasing network size possesses significant data collection challenges, which includes sensing, transmission coordination and sensor lifetime. To tackle these problems in-network compression techniques without centralized coordination are becoming important solutions. Data gathering and compressive sensing are the two approaches used earlier. To overcome the limitations of two aforementioned approaches, an adaptive mixed algorithm is used. An adaptive mixed algorithm is a combination of pack and forward (PF) and compressive sensing (CS). The proposed solution successfully minimizes the power consumption and the number of packets transmitted in the network. This approach is fully distributed in which each node autonomously takes a decision about the compression and forwarding scheme to minimize the number of packets to transmit. The method explained has been simulated using MATLAB and it has been established that an effective lifetime optimization could be achieved