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Energy analysis of symbiotic organisms search optimization based task scheduling algorithm

机译:基于共生生物搜索优化的任务调度算法能量分析

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Cloud computing is a technique of utilizing resources over internet to achieve a certain goal. With massive increase in the number of users and their variable demand of different services, hundreds to thousands of servers have to be deployed. Equally massive cooling systems are required to keep the servers working under normal temperatures. This leads to high CO2 emission and following current trends it is only expected to rise in the coming years. Thus cloud computing services are directly or indirectly contributing to global warming. Green computing is the solution to this problem in which same amount of weightage is given to makespan optimization as to the energy consumption and greenhouse gas emissions of a machine. In this paper, we perform energy analysis of a makespan-efficient algorithm Discrete Symbiotic organisms search (DSOS) and based on the results, we conclude that this algorithm can be made more energy-efficient which is also our area of future research.
机译:云计算是一种利用Internet资源来实现特定目标的技术。随着用户数量的大量增加以及他们对不同服务的不同需求,必须部署数百到数千台服务器。同样需要大量的冷却系统以使服务器在正常温度下工作。这导致高的二氧化碳排放,并且按照目前的趋势,预计仅在未来几年内会增加。因此,云计算服务直接或间接地导致了全球变暖。绿色计算是该问题的解决方案,在该问题中,对机器的能源消耗和温室气体排放给予相同的权重以进行制造跨度优化。在本文中,我们对一种有效跨度有效算法离散共生生物搜索(DSOS)进行了能量分析,并根据结果得出结论,该算法可以提高能效,这也是我们未来的研究领域。

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