Minimizing Total Busy Time with Application to Energy-Efficient Scheduling of Virtual Machines in IaaS Clouds

This paper investigates the energy-efficient virtual machine scheduling problems in IaaS clouds where users request multiple resources in fixed intervals and non-preemption for processing their virtual machines (VMs) and physical machines have bounded capacity resources. Many previous works are based on migration techniques to move on-line VMs from low utilization hosts and turn these hosts off to reduce energy consumption. However, the techniques for migration of VMs could not use in our case. The scheduling problem is NP-hard. Instead of minimizing the number used physical machines, we propose a scheduling algorithm EMinTRE-LFT to minimize the sum of total busy time of all physical machines that is equivalent to minimize total energy consumption. Our extensive simulations using parallel workload models in Parallel Workload Archive show that the proposed algorithm could reduce the total energy consumption compared with state-of-the-art algorithms including Tian's Modified First Fit Decreasing Earliest, Beloglazov's Power-Aware Best Fit Decreasing and vector binpacking norm-based greedy.