Confidence interval-based overload avoidance algorithm for virtual machine placement

被引:3
作者
Ahmadi, Javad [1 ]
Haghighat, Abolfazl Toroghi [2 ]
Rahmani, Amir Masoud [3 ]
Ravanmehr, Reza [1 ]
机构
[1] Islamic Azad Univ, Dept Comp Engn, Cent Tehran Branch, Tehran, Iran
[2] Islamic Azad Univ, Fac Comp & Informat Technol Engn, Qazvin Branch, Qazvin, Iran
[3] Natl Yunlin Univ Sci & Technol, Future Technol Res Ctr, Touliu, Taiwan
关键词
Green cloud; cloud computing; virtualization; dynamic consolidation; virtual machine placement; Overload avoidance; ENERGY-EFFICIENT; DYNAMIC CONSOLIDATION; VM CONSOLIDATION; DATA CENTERS; CLOUD; QUALITY; ENVIRONMENTS; CONSUMPTION; PREDICTION; SERVICE;
D O I
10.1002/spe.3127
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Virtualization plays an essential role in decreasing energy consumption and optimizing resource utilization by enabling the creation of virtual machines (VM) and their consolidation through live migration. Excessive migrations and a lack of required VMs are two critical factors in QoS degradation. The current consolidation approaches impose an intensive time complexity and cannot be used in large data centers with hundreds of hosts. This article proposes a framework for dynamic consolidation divided into a QoS-aware algorithm for overload avoidance and a power-aware algorithm for VM placement. To compute a safe zone criterion for any VM, relations were suggested by applying an interval estimate with a confidence level. By employing this criterion, the offered algorithm could guarantee the quality of service (QoS), particularly for specific VMs, while avoiding overhead. The VM placement algorithm is developed based on the maximum utilization of active hosts. It provides the capability to control the number of active hosts for the data center manager. The simulation results with real workloads revealed that the proposed framework could decline the amount of service level agreement violations by 78% and the number of migrations by 74%, and energy consumption by up to 13% in comparison with the best results of the benchmark algorithms. Hence, the application of this framework upgrades the QoS of data centers and declines their energy costs.
引用
收藏
页码:2288 / 2311
页数:24
相关论文
共 53 条
  • [1] Server consolidation techniques in virtualized data centers of cloud environments: A systematic literature review
    Abadi, Reza Mohamadi Bahram
    Rahmani, Amir Masoud
    Alizadeh, Sasan H.
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2018, 48 (09) : 1688 - 1726
  • [2] A Strategy for Live Migration of Virtual Machines in a Cloud Federation
    Addya, Sourav Kanti
    Turuk, Ashok Kumar
    Satpathy, Anurag
    Sahoo, Bibhudatta
    Sarkar, Mahasweta
    [J]. IEEE SYSTEMS JOURNAL, 2019, 13 (03): : 2877 - 2887
  • [3] A flexible approach for virtual machine selection in cloud data centers with AHP
    Ahmadi, Javad
    Haghighat, Abolfazl Toroghi
    Rahmani, Amir Masoud
    Ravanmehr, Reza
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2022, 52 (05) : 1216 - 1241
  • [4] An energy-efficient algorithm for virtual machine placement optimization in cloud data centers
    Azizi, Sadoon
    Zandsalimi, Maz'har
    Li, Dawei
    [J]. CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2020, 23 (04): : 3421 - 3434
  • [5] Managing Overloaded Hosts for Dynamic Consolidation of Virtual Machines in Cloud Data Centers under Quality of Service Constraints
    Beloglazov, Anton
    Buyya, Rajkumar
    [J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2013, 24 (07) : 1366 - 1379
  • [6] 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
  • [7] A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems
    Beloglazov, Anton
    Buyya, Rajkumar
    Lee, Young Choon
    Zomaya, Albert
    [J]. ADVANCES IN COMPUTERS, VOL 82, 2011, 82 : 47 - 111
  • [8] Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing
    Beloglazov, Anton
    Abawajy, Jemal
    Buyya, Rajkumar
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2012, 28 (05): : 755 - 768
  • [9] Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility
    Buyya, Rajkumar
    Yeo, Chee Shin
    Venugopal, Srikumar
    Broberg, James
    Brandic, Ivona
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2009, 25 (06): : 599 - 616
  • [10] CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
    Calheiros, Rodrigo N.
    Ranjan, Rajiv
    Beloglazov, Anton
    De Rose, Cesar A. F.
    Buyya, Rajkumar
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2011, 41 (01) : 23 - 50