Energy efficient information assured routing based on hybrid optimization algorithm for WSNs

Currently, wireless sensor networks (WSNs) are of significant, hot and challenging research area. WSN consists of numerous tiny wireless sensor nodes to communicate with each other with limited resources due to cost and size restrictions. Advancements in WSNs enable a wide range of environmental monitoring and object tracking applications. The major factor to be tackle in WSN the network lifetime and that actually depends on the efficiency of the routing protocol. A novel Biological Inspired Secure Autonomous Routing Protocol (BIOSARP) enhances Secure Real Time Load Distribution (SRTLD) with self-optimized routing mechanism that reduces neighbor discovery process at every hop. BIOSARP routing protocol depends on the optimal forwarding decision obtained by Ant Colony Optimization (ACO) algorithm. On top of ACO algorithm to provide preventive measures against abnormalities BIOSARP utilized artificial immune system (AIS). In this paper we present the energy efficiency and performance of ACO and AIS based hybrid nature adaptive computing method. Primarily, ACO based BIOSARP has been compared with SRTLD and onwards output of ACO algorithm and ACO+AIS algorithm is compared and analyzed in terms of delivery ratio, energy consumption and packet overhead. Network simulator 2 (NS2) has been utilized to perform the analysis. Our result shows that the hybrid nature adaptive optimization algorithm effectively shows better performance and increase network lifetime due to less energy consumption.