Green and FairWorkload Distribution in Geographically Distributed Datacenters

Abstract

To accommodate user applications and requests, service providers host large computer systems over an infrastructure of distributed datacenters in different geographical locations. Consequently, energy and power consumption increases, increasing electrical and cooling costs. Hence more attention is paid to green computing and exploiting renewable energy sources, along with decreasing electrical costs so that these datacenters are operated efficiently and effectively, with less impact on the environment. In this paper, a socially responsible scheduling scheme that distributes load from several regions to geographically distributed datacenters will be extended. Optimal electricity, social and latency costs will be sought within service level agreements, ensuring fairness between different regions and highlighting its importance.AdoptingstandardgradientmethodsandLagrangemultipliers,an optimization algorithm called Green-Fair is proposed that provides optimal selection of datacenters. Experimental results show the effectiveness of the Green-Fair algorithm in utilizing green energy sources, reducing the number of SLAviolations significantly, reducing latency costs and preserving fairness requirements by the SLAs while having little effect on the service providers’ overall operational costs.