TY - JOUR TI - Towards autonomic virtual machine management DO - https://doi.org/doi:10.7282/T33778F7 PY - 2010 AB - Virtual machine technologies are gaining wide acceptance in today’s era due to invaluable services in system management, server consolidation, and secure resource containment along with providing requisite application execution environment. Every virtual machine platform reduces dependence on hardware by fully or partially abstracting operating systems enabling flexible control of manipulation or migration of guest machines by manual system administration or reactive/proactive approaches to management. This dissertation focuses on resolving the resource reservation problem to help define a mathematical model and study interference within multiple virtual machines while trying to achieve load balancing and improve performance efficiency. Our goal is three-pronged. Firstly, we aim to understand the underlying support available for virtual machine migration and pursue new technologies or abstractions to improve efficiency and speed of the data transfer. Secondly, we carefully evaluate all the resources used by VMs for proper functioning and study the synchronization and multiplexing processes underneath which delineate when and where to migrate a virtual machine. Finally, we attempt to deduce the action to perform on running VMs (manipulation or resource configuration) so as to resolve the issue at hand. To achieve these goals, we follow a step-by-step procedure limiting the number of variable parameters and analyze the outcome of focal experiments. The results show that, using RDMA (Remote Direct Memory Access) to perform virtual machine migration can be used only in scenarios where the underlying hardware offers support for such transactions (eg. InfiniBand architecture) and such an abstraction over TCP/IP does not ameliorate efficiency of VM transfers. Further, a utility based function designed to analyze environment and application metrics and project an area of good/bad states on a map would require a plethora of parameters increasing its complexity. Considering VM re-distribution, one can predict the ideal number and time of migration of guest virtual machines on any configuration by gathering statistics from parallel migration for graphical analysis. Parallel VM migration gives us shorter average transfer time and higher latencies per VM. Pinning of virtual CPUs to VMs improves the performance efficiency of applications compared to sharing of CPUs. KW - Electrical and Computer Engineering KW - Virtual computer systems--Management KW - Computer network resources--Management LA - eng ER -