Energy Savings on a Cloud-Based Opportunistic Infrastructure

In this paper, we address energy savings on a Cloud-based opportunistic infrastructure. The infrastructure implements opportunistic design concepts to provide basic services, such as virtual CPUs, RAM and Disk while profiting from unused capabilities of desktop computer laboratories in a non-intrusive way. We consider the problem of virtual machines consolidation on the opportunistic cloud computing resources. We investigate four workload packing algorithms that place a set of virtual machines on the least number of physical machines to increase resource utilization and to transition parts of the unused resources into a lower power states or switching off. We empirically evaluate these heuristics on real workload traces collected from our experimental opportunistic cloud, called UnaCloud. The final aim is to implement the best strategy on UnaCoud. The results show that a consolidation algorithm implementing a policy taking into account features and constraints of the opportunistic cloud saves energy more than 40% than related consolidation heuristics, over the percentage earned by the opportunistic environment.