2016 IEEE 9th International Conference on Cloud Computing (2016)
San Francisco, California, USA
June 27, 2016 to July 2, 2016
Live virtual machine migration is an essential tool for dynamic resource management in current data centers. Many techniques have been developed to achieve this goalwith minimum service interruption. In this paper, we proposea pre-copy live VM migration using Distributed SharedMemory (DSM) computing model. The setup is built usingtwo identical computation nodes to construct the environmentservices architecture namely the virtualization infrastructure, the shared storage server, and the DSM and High PerformanceComputing (HPC) cluster. The custom DSM framework isbased on a low latency memory update Grappa. HPC clusterwith OPENMPI and MPI libraries support parallelization andauto-parallelization work load by using CPUs computationnodes. The DSM allows the cluster CPUs to access the samememory space pages resulting in a lower memory data updatesbased on locality attributes updates, which reduces the amountof data transferred through the network. This model achieves agood enhancement of the live VM migration metrics. Downtimeis reduced by 50% in the idle workload of Windows VM and66.6% in case of Ubuntu Linux idle workload. In general, thismodel not only reduces the downtime and the total amountof data sent, but also does not degrade other metrics like thetotal migration time and the application performance.
Program processors, Memory management, Linux, Virtual machining, Computational modeling, Virtualization, Servers
T. Daradkeh and A. Agarwal, "Distributed Shared Memory Based Live VM Migration," 2016 IEEE 9th International Conference on Cloud Computing(CLOUD), San Francisco, California, USA, 2016, pp. 826-830.