QoS enhanced distributed load balancing and task scheduling framework for wireless networks using hybrid optimisation algorithm

Abstract

Quality of service (QoS) is the main challenging issue in load balancing, task scheduling process in dynamic systems, such as grid system, peer-to-peer system, ad hoc networks, cloud computing system, pervasive computing system, and online social network system. The inefficient task scheduling process reduces QoS parameters, such as energy consumption, throughput, network lifetime, deadline missing ratio and schedule delay time. In this paper, we proposed QoS enhanced distributed load balancing, task scheduling frameworks for wireless networks (WNs) using hybrid optimisation algorithm (EDFHOA). We improve QoS of distributed frameworks by two phase system through an efficient clustering methodology using particle swarm optimisation (PSO) algorithm for load balancing in the first phase. A cuckoo search (CS) algorithm with load balanced for task scheduling in the second phase. The proposed two-phase hybrid algorithms enhance task scheduling, such as latency experienced by the balanced clustering, energy consumption, throughput, network lifetime, efficient resource utilisation and less processing time requirement and highly accurate than fault tolerant task allocation algorithm (FTAOA).