Journal
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Volume 32, Issue 2, Pages 1389-1400Publisher
IOS PRESS
DOI: 10.3233/JIFS-169136
Keywords
VM consolidation; VM placement; deadlock-free migration; Chicken Swarm Optimization
Categories
Funding
- National Key Research and Development Program of China [2016YFB1000903]
- National Natural Science Foundation of China [91118005, 91218301, 91018011, 61472315, 61502379, 61532015, 61532004]
- Natural Science Basic Research Plan in Shaanxi Province of China [2016JM6027, 2016JM6080]
- Online Education Research Foundation of MOE Research Center for Online Education [2016YB165, 2016YB169]
- MoE Innovative Research Team in University [IRT13035]
- Innovation Project of Shaanxi Province Key lab [2013SZS05p01]
- Project of China Knowledge Centre for Engineering Science and Technology
Ask authors/readers for more resources
Consolidation of services is one of the key problems in cloud data centers. It consists of two separate but related issues: Virtual machine (VM) placement and VM migration problems. In this paper, a VM consolidation scheme is proposed that turns the virtual machine consolidation (VMC) problem into a vector packing optimization problem based on deadlock-free migration (DFM) to minimize the energy consumptions. To solve this NP-hard and computationally infeasible for large data centers problem, a novel algorithm named Chicken Swarm Optimization based on deadlock-free migration (DFM-CSO) algorithm is proposed. The DFM-CSO algorithm is characterized by the 'one-step look-ahead with n-VMs migration in parallel (OSLA-NVMIP)' method, which carries out the VM migration validation and the rearrangement of target physical host, as well as records the migration order for each solution placement, so that VM transfer can be completed according to the migration sequence. The experimental results, for both real and synthetic datasets, show that the proposed algorithm with higher convergence rate is favourable in comparison with the other deadlock-free migration algorithms.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available