Honolulu, HI, USA USA
June 24, 2012 to June 29, 2012
This paper focuses on the problem of resource consolidation management within cloud computing environments and extends our previous IMPROMPTU model which demonstrated the viability of distributed Multiple Criteria Decision Analysis (MCDA) to provide a resource consolidation management that simultaneously achieves lower numbers of reconfiguration events and fewer service level agreement (SLA) violations as compared to other approaches. A core limitation of our previous work was that it only assessed the PROMETHEE II outranking-based MCDA method, leaving open the question of whether better outranking schemes exist and, more generally, what denotes the properties of good outranking approaches for this problem domain. This work addresses these deficiencies through extending the IMPROMPTU model to directly compare PROMETHEE II with ELECRE III and PAMSSEM II, two other well-known outranking-based MCDA schemes. An in-depth analysis of the generated simulation results are then used to highlight the core trade-offs between each of these MCDA approaches.
Virtual machining, Indexes, Software, Educational institutions, Analytical models, Context, Scalability, multiple criteria decision analysis, resource consolidation management
Yagiz Onat Yazir, Yagmur Akbulut, Roozbeh Farahbod, Adel Guitouni, Stephen W. Neville, Sudhakar Ganti, Yvonne Coady, "Autonomous Resource Consolidation Management in Clouds Using IMPROMPTU Extensions", CLOUD, 2012, 2013 IEEE Sixth International Conference on Cloud Computing, 2013 IEEE Sixth International Conference on Cloud Computing 2012, pp. 614-621, doi:10.1109/CLOUD.2012.105