A Workflow for Fast Evaluation of Mapping Heuristics Targeting Cloud Infrastructures

Abstract : Resource allocation is today an integral part of cloud infrastructures management to efficiently exploit resources. Cloud infrastructures centers generally use custom built heuristics to define the resource allocations. It is an immediate requirement for the management tools of these centers to have a fast yet reasonably accurate simulation and evaluation platform to define the resource allocation for cloud applications. This work proposes a framework allowing users to easily specify mappings for cloud applications described in the AMALTHEA format used in the context of the DreamCloud European project and to assess the quality for these mappings. The two quality metrics provided by the framework are execution time and energy consumption.
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Communication dans un congrès
DREAMCloud: Dynamic Resource Allocation and Management in Embedded, High Performance and Cloud Computing, Jan 2016, Prague, Czech Republic. 2nd International Workshop on Dynamic Resource Allocation and Management in Embedded, High Performance and Cloud Computing January 19, 2016, Prague, Czech Republic, 2016
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01265874
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  • HAL Id : lirmm-01265874, version 1
  • ARXIV : 1601.07420

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Roman Ursu, Khalid Latif, David Novo, Manuel Selva, Abdoulaye Gamatié, et al.. A Workflow for Fast Evaluation of Mapping Heuristics Targeting Cloud Infrastructures. DREAMCloud: Dynamic Resource Allocation and Management in Embedded, High Performance and Cloud Computing, Jan 2016, Prague, Czech Republic. 2nd International Workshop on Dynamic Resource Allocation and Management in Embedded, High Performance and Cloud Computing January 19, 2016, Prague, Czech Republic, 2016. 〈lirmm-01265874〉

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