Load distribution approaches for energy efficiency in cloud data centers

Abstract

Data centers are the backbone of cloud computing. These data newlinecenters significantly impact various sectors, such as business, education, newlinegovernment, information and communication systems, and social networking newlineactivities. Large-scale data centers perform the aforementioned activities. newlineSuch hyper-scale data centers use millions of kilowatts of electricity every newlineyear, causing huge energy consumption leading to increased energy cost and newlinecarbon footprint. To reduce the economic and environmental consequences, newlineenergy efficiency is one of the key factors for greening data centers, which newlinecomprises energy management, thermal management and environmental newlineawareness. newlineMotivated by the manifold approach for energy efficiency, this thesis newlinework considers energy aware, temperature aware and eco-aware load newlinedistribution approaches for efficient energy utilization. Generally, load newlinebalancing, scheduling and server consolidation are the mechanisms used for newlineimproving energy efficiency in the computing environment. Handling newlineworkload distribution is crucial to both mechanisms. This thesis work newlinepresents novel techniques, models and algorithms for efficient load newlinedistribution approaches to handle energy efficiency problems in cloud data newlinecenters. The aim is to optimize energy consumption in the context of green newlineaspects using efficient workload distribution and server consolidation newlineapproaches. newline