A Workflow for Fast Evaluation of Mapping Heuristics Targeting Cloud   Infrastructures
  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. 
Roman Ursu, Khalid Latif, David Novo, Manuel Selva, Abdoulaye Gamatie,   Gilles Sassatelli, Dmitry Khabi, Alexey Cheptsov
cs.DC