Virtual Machine Consolidation for NUMA Systems: A Hybrid Heuristic Grey Wolf Approach
| Autor: | Tiansheng Huang, Kangli Hu, Keqin Li, Like Ma, Weiwei Lin |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
021103 operations research
Computer science Heuristic (computer science) business.industry Distributed computing 0211 other engineering and technologies Particle swarm optimization 020206 networking & telecommunications Cloud computing 02 engineering and technology computer.software_genre Swarm intelligence System model Virtual machine 0202 electrical engineering electronic engineering information engineering Heuristics business computer TRACE (psycholinguistics) |
| Zdroj: | ICPADS |
| DOI: | 10.1109/icpads51040.2020.00079 |
| Popis: | Virtual machines consolidation is known as a powerful means to reduce the number of activated physical machines (PMs), so as to achieve energy-saving for the data centers. Although the consolidation technique is widely studied in non-NUMA systems, we could only trace a few studies targeting NUMA systems. But the virtual machines (VMs) deployment of NUMA systems is quite different from that of non-NUMA systems. More specifically, consolidating VMs in NUMA systems need to decide both target physical machines and NUMA architectures to host the VMs, and more complicated constraints originated from the real usage of NUMA systems that need to be considered. Being motivated by these challenges, we in this paper formally derive the system model according to the real business model of NUMA systems and based on which, we propose a hybrid heuristics swarm intelligence optimization algorithm HHGWA for an efficient solution. To do the evaluation, extensive simulations that integrate real VM and PM information are conducted, the result of which indicates a superior performance of our proposed algorithm. |
| Databáze: | OpenAIRE |
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