文章基本信息

标题：PGA Scheduling with Cloud Computing
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作者：Rachhpal Singh ; Harish Kumar Sharma
期刊名称：International Journal of Computer Applications and Information Technology
印刷版ISSN：2278-7720
出版年度：2014
卷号：6
期号：2
页码：117-122
出版社：Mahadev Educational Society
摘要：Execution of a large task and then further spliting the task into small multiple sub tasks that execute simultaneously and makes the exacution more fast is the concept of parallel computing. Faster output can be drawn with the capability of dividing the large task into modules. It is more beneficial and effective for large number of computation under some constraints like time, space, complexity constraints etc. Another crucial step in handling the parallel computing is the assignment of a set of tasks in the parallel system environment and makes the makespan set the execution in such a way that the total execution time is minimized. Cloud computing is the challanging job in the task scheduling. Efficient execution of the job schedule in p arallel environment with cloud schedular that takes the structure of the application and the performance characteristics is proposed in this algorithm. There are number of algorithms in solving the task scheduling have been proposed. Such type of problem is heuristic NP-Hard problem. Research proposes Parallel Genetic Algorithm (PGA) to schedule tasks parallely on hetrogeneous parallel environment using genetic approach. It is a heuristic technique. In this paper the scheduling of jobs is a major problem. It includes - mapping of the task optimally, search of an optimal parallel system and to set sequence of job execution. The mechanism for the optimization of all the these components of scheduling techniques with the help of cloud schedular and genetic approach is experimanted and its perfo rmance is evaluated in comparison with some scheduling algorithms like First Come First Serve (FCFS), Round Robin (RR) and optimal scheduling and optimized result be evaluated.
关键词：Parallel Gentic Approach; DAG (Directed acyclic graph); Cloud computing; Task Scheduling.