2011/12/16 by Michael Menzel, Rajiv Ranjan, Menzel, Michael +1
Computer Science · #Cloud Computing and Resource Management #Distributed #FOS: Computer and information sciences #Parallel #Service-Oriented Architecture and Web Services #Software System Performance and Reliability #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.1112.3880
technical report
openalex publication_date 2011/12/16 · arxiv created 2012/02/06 · arxiv updated 2012/02/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
One of the key problems in migrating multi-component enterprise applications\nto Clouds is selecting the best mix of VM images and Cloud infrastructure\nservices. A migration process has to ensure that Quality of Service (QoS)\nrequirements are met, while satisfying conflicting selection criteria, e.g.\nthroughput and cost. When selecting Cloud services, application engineers must\nconsider heterogeneous sets of criteria and complex dependencies across\nmultiple layers impossible to resolve manually. To overcome this challenge, we\npresent the generic recommender framework CloudGenius and an implementation\nthat leverage well known multi-criteria decision making technique Analytic\nHierarchy Process to automate the selection process based on a model, factors,\nand QoS requirements related to enterprise applications. In particular, we\nintroduce a structured migration process for multi-component enterprise\napplications, clearly identify the most important criteria relevant to the\nselection problem and present a multi-criteria-based selection algorithm.\nExperiments with the software prototype CumulusGenius show time complexities.\n