Research Area:  Cloud Computing

Abstract:

In this paper, a new cloud computing task-scheduling algorithm that introduces min-min and max-min algorithms to generate initialization population, selects task completion time and load balancing as double fitness functions, and improves the quality of initialization population, algorithm searchability and convergence speed, was proposed. The paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

Keywords:  
Cloud Computing; Eiga Scheduling; Genetic Algorithm; Max-Min Algorithm; Min-Min Algorithm; Task Scheduling

Author(s) Name:  Weiqing, G.E, Yanru, Cui

Publisher name:  Bentham Science Publishers

DOI:  10.2174/2352096513999200424075719

Volume Information:  Volume 14,(2021)

Paper Link:   https://www.ingentaconnect.com/content/ben/raeeng/2021/00000014/00000001/art00005;jsessionid=f21eafalahaab.x-ic-live-01