01419nam a2200121Ia 4500008004100000041001200041082001600053100009900069245008000168260000900248510094800257650009201205231221s9999    xx            000 0 und d  aEnglish  aCPCS19-1861  aPriyanka Bhandia. Pavan Yekbote. Ravi Shreyas. Nikhil Singh. Phalachandra H L. Dinkar Sitaram. 0aDCSim: Cooling Energy Aware VM Allocation framework for a Cloud Data Center  c2019  aExplosion of digital content has resulted in large amounts of resources being provisioned and managed for various applications in cloud Data Centers. Energy consumption in these large Cloud Data Centers is a rising concern, accounting for 1.3% of the worlds electricity consumption [1]. Data Center cooling accounts for 40% of this energy consumption [2]. Of the various mechanisms available for studying the energy consumption in Data Centers, a simulation based approach is quite popular. In this paper, we propose DCSim, a configurable extension to CloudSim, a popularly used cloud infrastructure and simulation framework. CloudSim provides coarse power models to calculate total energy consumption in a Data Center for a given workload, but has no provision to factor in the Data Center topology and current cooled area into this power model. This makes building intelligent cooling energy aware allocation policies in CloudSim difficult.   a     Green Computing     ,     Cloud Computing     ,     Modeling     ,     Simulation