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Cloud computing is a newly emerging distributed computing which is evolvedfrom Grid computing. Task scheduling is the core research of cloud computingwhich studies how to allocate the tasks among the physical nodes so that thetasks can get a balanced allocation or each task's execution cost decreases tothe minimum or the overall system performance is optimal. Unlike the previoustask slices' sequential execution of an independent task in the model of whichthe target is processing time, we build a model that targets at the responsetime, in which the task slices are executed in parallel. Then we give itssolution with a method based on an improved adjusting entropy function. Atlast, we design a new task scheduling algorithm. Experimental results show thatthe response time of our proposed algorithm is much lower than thegame-theoretic algorithm and balanced scheduling algorithm and compared withthe balanced scheduling algorithm, game-theoretic algorithm is not necessarilysuperior in parallel although its objective function value is better.

A Task Allocation Schema Based on Response Time Optimization in Cloud Computing