Optimization of Multi-Dimensional Metrics through Task Scheduling in Cloud Computing Systems (original) (raw)

Cloud-based data centers consume a considerable amount of energy, which is an expensive system. The virtualization technique helps to overcome various issues including the energy issue. Because of the dynamic nature of workload, task consolidation is an effective technique to decrease the total number of servers and unnecessary migrations and consequently optimize energy. Effective task allocation techniques act as a key issue to optimize several performance parameters in the cloud system. This paper presents a novel task consolidation technique to achieve energy-makespan-throughput optimally balanced in the cloud data center. We evaluate the performance of our proposed algorithm using simulation analysis in Java-based CloudSim simulator environments. Results of performance evaluation certify that our proposed algorithm has reduced the energy consumption as compared to existing standard algorithms, and optimized the makespan and throughput of the cloud data center. Keywords—Cloud co...