Name
Abstract | ||
|---|---|---|
Much effort in the current literature has been put towards methods and implementations to solve Resource Consolidation Management (RCM) problems in the cloud setting. A vast number of proposed solutions appears to be designed for different variants of the RCM problem. This makes the comparison of approaches challenging. We propose a new framework that facilitates mapping RCM solutions to their RCM problem definitions. Our framework allows a solution to be assigned to its RCM problem definition by means of answering a set of questions specific to RCM problems. Our framework can be used to (1) specify problem descriptions, (2) establish optimal solutions and providing theoretical benchmarks, (3) provide a platform allowing formal complexity analysis of RCM problems and (4) facilitate a healthy discussion about the essence of RCM and evaluations of different solutions. We show how our proposed framework can be applied in form of case studies depicting four approaches from the literature. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CLOUD.2012.114 | Cloud Computing |
Keywords | Field | DocType |
cloud computing,formal concept analysis,pattern classification,resource allocation,RCM problem,RCM problem definition,RCM solution mapping,classification framework,cloud computing,cloud setting,formal complexity analysis,problem description,resource consolidation management problem,resource consolidation management,theoretical benchmarks,unified framework | Resource management,Software engineering,Computer science,Implementation,Resource allocation,Consolidation (soil),Formal concept analysis,Management science,Cloud computing,Distributed computing | Conference |
ISSN | ISBN | Citations |
2159-6182 | 978-1-4673-2892-0 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steven Lonergan | 1 | 0 | 0.68 |
| Yağız Onat Yazır | 2 | 4 | 1.76 |
| Ulrike Stege | 3 | 334 | 34.26 |