Hybrid Genetic Algorithm and African Buffalo Optimization (HGAABO) Based Scheduling in ZigBee Network

摘要

In Wireless sensor network (WSNs) unstable battery consumption is a major challenge to overcome these sensors should be active for a preferred duration so the network's lifetime should be essentially prolonged with less power consumption. While processing the data, the PAN coordinator transmits the beacon frame to its cluster coordinators and the sensor nodes receive the beacon frames from cluster coordinates periodically. During this process collision occurs, it results in poor performance. Various meta-heuristic optimization techniques have been proposed to resolve the optimization problems. The aim of this paper is to analysis the performance of mobility models in IEEE 802.15.4 ZigBee MAC using NS2.34. The proposed method HGAABO is a hybrid new algorithm that combines the genetic algorithm (GA) and African Buffalo Optimization (ABO) to optimize the path selection in the network. The main conclusions of this research include two parameters that were energy and delay. The algorithm is used to identify a set of routes that can satisfy the delay constraints and then select a reasonably good route through the proposed algorithm. The proposed approach is compared against the original GA and GWO on problems in terms of a set of performance metrics. The simulation results showed that the proposed approach demonstrated a better performance than the compared algorithms.