An Improved Multi-objective Optimization Algorithm Based on NPGA for Cloud Task Scheduling
YANG Yan
Abstract：As cloud computing continues to evolve ,task scheduling under the traditional single‐objective optimization has been unable to meet the user's requirements for quality of service .This paper selects the running time and cost and load balance of establishing a multi‐objective optimization of cloud task scheduling model ,an improved multi‐objective niche Pare‐to genetic algorithm(NPGA) is proposed to speed up evolution and avoid premature convergence through a similar task se‐quence crossover(STOX) operating and shift mutation .In addition ,the size of comparison set and niche radius are selected a‐daptively to improve convergence speed .Simulation results show that improved NPGA algorithm is better to maintain diver‐sity and distribution of Pareto optimal solutions in the cloud scheduling .
Keywords：multi-objective optimizationcloud task schedulingniche Pareto genetic algorithmquality of service
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 1196-1201,1216 )