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Zhang, Q., Zhani, M.F., Zhang, S., Zhu, Q., Boutaba, R. and Hellerstein, J.L. (2012) Dynamic Energy-Aware Capacity Provisioning for Cloud Computing Environments. Proceedings of the 9th International Conference on Autonomic Computing, ICAC’12, 145-154.
http://dx.doi.org/10.1145/2371536.2371562

has been cited by the following article:

• TITLE: Residual Resource Defragmentation Based on ECRC (Enhanced Cloud Resource Consolidating)

  AUTHORS: G. Soniya Priyatharsini, N. Malarvizhi

  KEYWORDS: Server Consolidation, Residual Resource Defragmentation, Server Sprawl, Resource Pooling

  JOURNAL NAME: Circuits and Systems, Vol.7 No.10, August 19, 2016

  ABSTRACT: In cloud computing, server consolidation is the part where very few persons go through the same. By consolidating the unused server space, memory can be reused for another data allocation. The objective of this paper is to improve resource utilization. Residual resource fragmentation refers to the state of the data center where sufficient amount of residual resources are available for any new VM allocation. To achieve this, there are three methods followed here. Active physical servers are identified. Then the maximum utilization of the resources is found out. Finally the resources are allocated and scheduled using the developed algorithm. In this work, we have proposed a new algorithm enhanced cloud consolidating algorithm. This algorithm improves some of the qualities of the cloud consolidating algorithm. Here the allocation technique is based on the cost and the memory.