2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS) (2015)
Dec. 11, 2015 to Dec. 13, 2015
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DSDIS.2015.36
Cloud computing has been widely used in every social field. The problem of energy consumption in a cloud computing environment has brought cost pressure to service providers and affected the natural environment. However, the reasonable and efficient scheduling of resources could save a lot of energy for cluster. Meanwhile, it's necessary for us to take into account of the emergent needs of every consumer. So the resource scheduling is often regarded as a multi-objective problem with the optimization of energy consumption and time cost. We redefine the problem in this paper and set up a multi-objective optimization model, and the parallel computing is improved on the basis of bee colony algorithm. Furthermore, multi-objective problem optimization based on fast non-dominated sorting method is used in parallel environment. Experimental results show that the proposed algorithm can save energy, reduce the execution time of tasks and have very good stability in parallel environment.
Optimization, Servers, Energy consumption, Cloud computing, Sorting, Resource management, Sociology
T. Wen, Z. Zhang and M. Wang, "A Parallel Bee Colony Algorithm for Resource Allocation Application in Cloud Computing Environment," 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS), Sydney, Australia, 2015, pp. 153-160.