An Autonomous Network Aware VM Migration Strategy in Cloud Data Centres

被引:9
作者
Duggam, Martin [1 ]
Duggan, Jim [1 ]
Howley, Enda [1 ]
Barrett, Enda [1 ]
机构
[1] Natl Univ Ireland, Galway, Ireland
来源
2016 INTERNATIONAL CONFERENCE ON CLOUD AND AUTONOMIC COMPUTING (ICCAC) | 2016年
关键词
Live Migration; Bandwidth; Reinforcement Learning; Network Flow;
D O I
10.1109/ICCAC.2016.9
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Live virtual machine migration can have a major impact on how a cloud system performs, as it can consume significant amounts of network resources such as bandwidth. A virtual machine migration occurs when a host becomes over-utilised or underutilised. Migration contributes to an increase in consumption of network resources which leads to longer migration times and ultimately has a detrimental effect on the performance of a cloud system. In this paper, we propose an autonomous network aware virtual machine migration strategy that observes the current demand level of a network and performs appropriate actions based on what it is experiencing. The Artificial Intelligence technique known as Reinforcement Learning acts as a decision support system, enabling an agent to learn an optimal time to schedule a virtual machine migration depending on the current network traffic demand. We show that an autonomous agent can learn to utilise available network resources when network saturation occurs at peak times.
引用
收藏
页码:24 / 32
页数:9
相关论文
共 26 条
  • [1] Akoush Sherif, 2010, Proceedings 18th IEEE/ACM International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS 2010), P37, DOI 10.1109/MASCOTS.2010.13
  • [2] [Anonymous], 2007, P 4 USENIX C NETW SY
  • [3] [Anonymous], 1998, REINFORCEMENT LEARNI
  • [4] A View of Cloud Computing
    Armbrust, Michael
    Fox, Armando
    Griffith, Rean
    Joseph, Anthony D.
    Katz, Randy
    Konwinski, Andy
    Lee, Gunho
    Patterson, David
    Rabkin, Ariel
    Stoica, Ion
    Zaharia, Matei
    [J]. COMMUNICATIONS OF THE ACM, 2010, 53 (04) : 50 - 58
  • [5] Towards Adaptive Policy-based Management
    Bahati, Raphael M.
    Bauer, Michael A.
    [J]. PROCEEDINGS OF THE 2010 IEEE-IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM, 2010, : 511 - 518
  • [6] Applying reinforcement learning towards automating resource allocation and application scalability in the cloud
    Barrett, Enda
    Howley, Enda
    Duggan, Jim
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2013, 25 (12) : 1656 - 1674
  • [7] Beloglazov Anton, 2010, Proceedings 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid), P826, DOI 10.1109/CCGRID.2010.46
  • [8] Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers
    Beloglazov, Anton
    Buyya, Rajkumar
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2012, 24 (13) : 1397 - 1420
  • [9] Chen H, COORDINATING VIRTUAL
  • [10] Chen J., 2012, NETWORK PERFORMANCE