• cloud datacenter;
  • virtual machine;
  • power management;
  • consolidation;
  • live migration;
  • performance model;
  • reliability


Server consolidation using virtualization technologies allow large-scale datacenters to improve resource utilization and energy efficiency. However, most existing consolidation strategies solely focused on balancing the tradeoff between performance service-level-agreements (SLAs) desired by cloud applications and energy costs consumed by hosting servers. With the presence of fluctuating workloads in datacenters, the lifetime and reliability of servers under dynamic power-aware consolidation could be adversely impacted by repeated on–off thermal cycles, ware-and-tear and temperature rise. In this paper, we propose a Reliability-Aware server Consolidation stratEgy, named RACE, to address when and how to perform energy-efficient server consolidation in a reliability-friendly and profitable way. The focus is on the characterization and analysis of this problem as a multi-objective optimization, by developing a utility model that unifies multiple constraints on performance SLAs, reliability factors and energy costs in a holistic manner. An improved grouping genetic algorithm is proposed to search the global optimal solution, which takes advantage of a collection of reliability-aware resource buffering and virtual machines-to-servers re-mapping heuristics for generating good initial solutions and improving the convergence rate. Extensive simulations are conducted to validate the effectiveness, scalability and overhead of RACE—in improving the overall utility of datacenters while avoiding unprofitable consolidation in the long term—compared with pMapper and PADD strategies for server consolidation. Copyright © 2013 John Wiley & Sons, Ltd.