
doi: 10.1109/mcc.2016.48
handle: 11386/4678346 , 11591/359989 , 10722/225996
The elastic provisioning of resources and the capability to adapt to changing resource demand and environmental conditions on-the-fly are, probably, key success factors of cloud computing. Live migration of virtual resources is of pivotal importance in achieving such key properties. However, the ability to effectively and efficiently determine which resource to be migrated and where, by satisfying proper objectives and constraints, remains a research challenge. The existing literature is generally based on metaheuristics running a central resolver. Such an approach is not suitable because it only considers the quality-of-service aspect during the decision-making performance while ignoring the regulatory challenges. This column highlights the regulatory challenges associated with the cross-border dataflow implication of migration and stresses the need to adopt alternative decision approaches.
cloud computing; cloud migration; game theory; standards; Software; Computer Science (miscellaneous); Computer Science Applications1707 Computer Vision and Pattern Recognition; Computer Networks and Communications, cloud computing; cloud migration; game theory; standards; Computer Science (miscellaneous); Computer Networks and Communications; Computer Science Applications1707 Computer Vision and Pattern Recognition; Software
cloud computing; cloud migration; game theory; standards; Software; Computer Science (miscellaneous); Computer Science Applications1707 Computer Vision and Pattern Recognition; Computer Networks and Communications, cloud computing; cloud migration; game theory; standards; Computer Science (miscellaneous); Computer Networks and Communications; Computer Science Applications1707 Computer Vision and Pattern Recognition; Software
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
