Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search-Based Request Partitioning
Issue No. 06 - June (2013 vol. 24)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2012.204
Aris Leivadeas , National Technical University of Athens (NTUA), Athens
Chrysa Papagianni , National Technical University of Athens (NTUA), Athens
Symeon Papavassiliou , National Technical University of Athens (NTUA), Athens
The cloud represents a computing paradigm where shared configurable resources are provided as a service over the Internet. Adding intra- or intercloud communication resources to the resource mix leads to a networked cloud computing environment. Following the cloud infrastructure as a Service paradigm and in order to create a flexible management framework, it is of paramount importance to address efficiently the resource mapping problem within this context. To deal with the inherent complexity and scalability issue of the resource mapping problem across different administrative domains, in this paper a hierarchical framework is described. First, a novel request partitioning approach based on Iterated Local Search is introduced that facilitates the cost-efficient and online splitting of user requests among eligible cloud service providers (CPs) within a networked cloud environment. Following and capitalizing on the outcome of the request partitioning phase, the embedding phase—where the actual mapping of requested virtual to physical resources is performed can be realized through the use of a distributed intracloud resource mapping approach that allows for efficient and balanced allocation of cloud resources. Finally, a thorough evaluation of the proposed overall framework on a simulated networked cloud environment is provided and critically compared against an exact request partitioning solution as well as another common intradomain virtual resource embedding solution.
Substrates, Cloud computing, Partitioning algorithms, Availability, Special issues and sections, Scalability, virtualized infrastructures, Cloud computing, resource mapping
S. Papavassiliou, C. Papagianni and A. Leivadeas, "Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search-Based Request Partitioning," in IEEE Transactions on Parallel & Distributed Systems, vol. 24, no. , pp. 1077-1086, 2013.