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evolutionizing technology called Cloud Computing. Cloud Computing (CC) facilitate from corporate sector to start-ups, to use the on-demand IT services without concerning about the management, security and maintenance of the infrastructure. Establishing all these services using highly powered Cloud Data Centers (DCs), there is a considerable amount of energy consumption in CC environment that can’t be neglected. Indeed, the current energy consumption analyzed by ICT (Information Communication Technologies) is estimated to be more than 10% of the worldwide consumption, expecting to elevate in upcoming years. These high end DCs utilizes the cloud energy to accomplish requests or tasks generated by the users. This energy consumption not only effects the economies of governments and companies, but also the planetary environment through carbon emissions. Recent research indicates that towards the ending of 2020, the carbon emission footprints will elevate by 20%, making the energy efficient cloud systems one of today’s major challenge. This thesis basically attempts to design the possible efficient solutions which can be adopted to reduce these carbon footprints and practice a green cloud computing environment. Keywords: Cloud Computing (CC) Environment, Data Centers (DCs), Clustering, Energy-Aware Scheduling, ANOVA, Tukey’s HSD.