Deadline aware virtual machine scheduler for grid and cloud computing
Khalid, Omer, Maljevic, Ivo, Anthony, Richard, Petridis, Miltos, Parrott, Kevin and Schulz, Markus (2010) Deadline aware virtual machine scheduler for grid and cloud computing. In: Proceedings: 24th IEEE International Conference on Advanced Information Networking and Applications Workshops WAINA 2010. IEEE Computer Society, Conference Publications Services, Los Alamitos, CA, USA, pp. 85-90. ISBN 978 0 7695 4019 1 (doi:10.1109/WAINA.2010.107)Full text not available from this repository.
Virtualization technology has enabled applications to be decoupled from the underlying hardware providing the benefits of portability, better control over execution environment and isolation. It has been widely adopted in scientific grids and commercial clouds. Since virtualization, despite its benefits incurs a performance penalty, which could be significant for systems dealing with uncertainty such as High Performance Computing (HPC) applications where jobs have tight deadlines and have dependencies on other jobs before they could run. The major obstacle lies in bridging the gap between preformance requirements of a job and performance offered by the virtualization technology if the jobs were to be executed in virtual machines. In this paper, we present a novel approach to optimize job deadlines when run in virtual machines by developing a deadline-aware algorithm that responds to job execution delays in real time, and dynamically optimizes jobs to meet their deadline obligations. Our approaches borrowed concepts both from signal processing and statistical techniques, and their comparative performance results are presented later in the paper including the impact on utilization rate of the hardware resources.
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