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Research on Task Scheduling Strategy of Cloud Computing Based on MPSO Algorithm
Author: ZhangMengHua
Tutor: LiuWanJun
School: Liaoning Technical University
Course: Computer Software and Theory
Keywords: task scheduling cloud computing PSO algorithm CloudSim platform
CLC: TP3
Type: Master's thesis
Year: 2011
Downloads: 264
Quote: 2
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Abstract
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Task (job) scheduling is the one of key technologies of cloud computing. The paper focuses on the cloud task scheduling strategy, and its goal is to reduce application execution costs and improve the efficiency of the cloud system. For characteristics of Particle Swarm Optimization (PSO) Algorithm, thinking over the optimization problem of task scheduling and resource loading balance of cloud computing, the paper proposes a model of cloud task scheduling based on modified Particle Swarm Optimization (MPSO) algorithm. It introduces dynamic multi-group collaboration and the reverse of the flight of mutation particles to the PSO algorithm, and the experiment shows that the algorithm can control the global search and local search effectively, as far as possible to avoid falling local optimum. The paper uses the MPSO algorithm in the task scheduling of cloud computing, and solves the multi-objective optimization problem of searching task-resource mapping match. It carries out simulation experiments in CloudSim platform, which is a cloud computing analog simulator, and it compares experimental results of CloudSim original scheduling algorithm, standard PSO algorithm and MPSO algorithm. The cloud task scheduling based on MPSO algorithm in the paper is better than the existing methods of CloudSim platform. Under the premise of the efficiency of cloud systems, it greatly reduces the cost of task execution and meets the expected results.
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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology
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