Time-Aware VMFlow Placement, Routing, and Migration for Power Efficiency in Data Centers

Increased power usage and network performance variation due to best-effort bandwidth sharing significantly affect tenancy cost, cloud adoption, and data center efficiencies. In this paper, we propose a novel time-aware request model which enables tenants to specify an estimated required time-duration, in addition to their required server resources for Virtual Machines (VMs) and network bandwidth for their communication. We investigate the VM-placement and routing problem, which allocates both server and network resources for the specified time-duration, to provide resource guarantees. Further, we exploit VM-migration while considering its power consumption overhead, to improve power saving and resource utilization. Using the multi-component utilization-based power model, we formulate the problem as an optimization problem that maximizes the acceptance rate while consuming as low power as possible. We develop fast online heuristics that allocate resources for requests, considering their duration and bandwidth demand. We also develop migration policies augmenting these heuristics. For migration heuristics, we propose server-migration and switch-migration approaches, which migrate the VMs between the powered-on servers only if their migrations result in turning-off at least one server and switch, respectively. We demonstrate the effectiveness of the proposed heuristics in terms of power saving, acceptance ratio, and migration overhead using comprehensive simulation results.

I. Introduction

Power-efficiency and predictability in data centers have become matters of concern to cloud service providers for maximizing their economic benefits. While increased power bills, carbon emissions and power supply limitations significantly affect their ability to support more tenants [1]– [7], unpredictable tenancy costs and performance concerns have deterred many potential tenants from adopting cloud services [8]– [12]. Thus, to save power as well as attract and support more tenants, cloud providers require power-efficient resource allocation algorithms capable of providing resource guarantees.