A swarm intelligence based clustering technique with scheduling for the amelioration of lifetime in sensor networks

Abstract

The Wireless Sensor Networks (WSNs) are used in numerous application fields which include Predictive maintenance, High confidence Transport and Asset Tracking, Smart Buildings, Improved Safety and Security, etc. Although numerous methods have been presented, WSN needs productive convention of the network resources for the entire network operation and the interference with the nodes in the network prompts extensive measures of both the energy and time consumptions. The existing methods have mitigated this issue with the use of clustering mechanisms still their performances decreased based on the cluster management and time synchronization under large monitoring area To overcome these issues, a graph based model called Interferenceaware Energy-aware Multitask Scheduling Heuristic (IEMTSH) has been proposed for efficiently using these resources in the interference aware WSN environment and this method schedules the multitasks done by every node in the WSN. The proposed work comprises three steps. First, the entire network topology is changed into mixed graph for dealing with the multitask schedule the nodes to minimize the interference and energy among them. Second, Schedule the computation and communication nodes by the methodology of Initial Schedule is constructed and finally, the unused slacks are picked up towards the end of the second stage to reduce the energy and time consumptions of the network. But the network lifetime is degraded and the latency of the network is maximized. To overcome these issues, Artificial Bee Colony (ABC) based clustering with distributed scheduling has been proposed for experimentation. In the first phase, ABC based clustering is performed in the entire cluster groups to observe the optimal target node. newline