Enhancement of energy efficiency in Green cloud computing

Abstract

Cloud computing is one of the prominent technology in the networking newlinearea. Cloud computing provides various types of services. Vast amounts of newlineresources are accommodated in the cloud data center. The cloud data center is one newlineof the most energy-consuming areas in cloud computing. Energy consumption is newlinecaused by inefficient resource utilization. The efficient Data Center topological newlinearchitecture may improve the efficiency of resource utilization and energy newlineefficiency. newlineThis research work focuses on the improvement of the energy newlineefficiency on the cloud data center servers. This research achieves energy newlineefficiency via proper resource utilization. This thesis contains the following newlineframework. newlineTo implement Energy Efficient Virtual Round Robin (EEVRR) newlinescheduling algorithm with FAT-Tree topological architecture. newlineTo implement Starvation aware scheduling, Shortest Round robin newlineVibrant Quantum (SRVQ) algorithm with DVFS. newlineTo implement Hybrid Artificial Bee Colony (HABC) algorithm with newlineCART flow scheduling. newlineTo implement the Adaptive Cache Replacement (ACR) algorithm to newlineimprove the energy efficiency in cloud storage such as (PACS). newlineThe EEVRR algorithm gives higher priority to the least timeconsuming newlineprocess, so it improves the QoS parameters as well as improves the newlineenergy efficiency. The EEVRR algorithm combined with the Threshold-based newlineload balancing technique; these are incorporated into the FAT-Tree topological newlinearchitecture. The FAT-Tree architecture cut off 50% of the power consumption in newlinecloud data centers. The experiments were carried out into the Cloud Sim newlinesimulator. The EEVRR algorithm provided the best results compared to other newlinealgorithms. newline