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Issue No.06 - June (2013 vol.62)
pp: 1060-1071
C. Papagianni , Sch. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Athens, Greece
A. Leivadeas , Sch. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Athens, Greece
S. Papavassiliou , Sch. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Athens, Greece
V. Maglaris , Sch. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Athens, Greece
Cristina Cervello-Pastor , Dept. of Telematics Eng., Univ. Politεcnica de Catalunya, Barcelona, Spain
Alvaro Monje , Dept. of Telematics Eng., Univ. Politεcnica de Catalunya, Barcelona, Spain
Cloud computing builds upon advances on virtualization and distributed computing to support cost-efficient usage of computing resources, emphasizing on resource scalability and on demand services. Moving away from traditional data-center oriented models, distributed clouds extend over a loosely coupled federated substrate, offering enhanced communication and computational services to target end-users with quality of service (QoS) requirements, as dictated by the future Internet vision. Toward facilitating the efficient realization of such networked computing environments, computing and networking resources need to be jointly treated and optimized. This requires delivery of user-driven sets of virtual resources, dynamically allocated to actual substrate resources within networked clouds, creating the need to revisit resource mapping algorithms and tailor them to a composite virtual resource mapping problem. In this paper, toward providing a unified resource allocation framework for networked clouds, we first formulate the optimal networked cloud mapping problem as a mixed integer programming (MIP) problem, indicating objectives related to cost efficiency of the resource mapping procedure, while abiding by user requests for QoS-aware virtual resources. We subsequently propose a method for the efficient mapping of resource requests onto a shared substrate interconnecting various islands of computing resources, and adopt a heuristic methodology to address the problem. The efficiency of the proposed approach is illustrated in a simulation/emulation environment, that allows for a flexible, structured, and comparative performance evaluation. We conclude by outlining a proof-of-concept realization of our proposed schema, mounted over the European future Internet test-bed FEDERICA, a resource virtualization platform augmented with network and computing facilities.
Virtualization, Quality of service, Cloud computing, Computational modeling, Resource management,quality of service, Federated infrastructures, resource allocation, resource mapping, virtualization, cloud computing
C. Papagianni, A. Leivadeas, S. Papavassiliou, V. Maglaris, Cristina Cervello-Pastor, Alvaro Monje, "On the optimal allocation of virtual resources in cloud computing networks", IEEE Transactions on Computers, vol.62, no. 6, pp. 1060-1071, June 2013, doi:10.1109/TC.2013.31
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