Chicken Swarm Optimization in Task Scheduling in Cloud Computing

Abstract

In order to solve the problem of low efficiency in resource scheduling in cloud computing, an improved chicken swarm optimization (CSO) is proposed for task scheduling. Firstly, the concept of opposition-based learning is introduced to initialize the chicken population and improve the global search ability. Secondly, the concepts of the weight value and learning factor in particle swarm optimization (PSO) are introduced to improve the positions of chickens, and the individual positions of chickens are optimized. Thirdly, the overall individual positions of the CSO are optimized by the difference algorithm. Finally, the possible cross-boundary of individual positions in the algorithm is prevented as a whole by boundary processing. In the simulation experiment, the optimized CSO is compared with the basic CSO, PSO, and ant colony optimization (ACO) in terms of completion time, cost, energy consumption, and load balancing, and good results are achieved.

Task Scheduling in a Cloud Environment Based on Meta-Heuristic Approaches: A Survey

“…The second is chemical reaction optimization, which is inspired by chemical reactions. Cuckoo Search Algorithm (CSA) [34][35][36][37], Chicken Swarm Optimization (GSO) [38][39][40][41][42], Genetic Algorithm (GA) [44][45][46][47][48], BA [50][51][52][53], Whale Optimization Algorithm (WOA) [55][56][57][58][59][60][61], and Gray Wolf Optimization (GWO) [63][64][65][66][67][68][69][70] are examples of nature-inspired algorithms. A brief summary of the mentioned methods is given in Tables 5 and 6.…”

“…. Multi objective [35][36][37] Single objective [39,40] Multi objective [41,42] Multi objective [44][45][46][47][48] Single objective [50,52,53] Multi objective [51] Single objective [56,58] Multi objective [55,57,[59][60][61] Single objective [65,68] Multi objective [63,64,66,67,69,70] Chemistry-based Physics-based Nature-based…”

“…For an efficient resource schedule, an improved CSO is presented by Han [40]. First, opposition-based learning (OBL) is used to initialize the chicken population and improve the global search ability.…”