Market-based autonomous resource and application management in private clouds

被引:2
|
作者
Costache, Stefania [1 ]
Kortas, Samuel [1 ,4 ]
Morin, Christine [2 ]
Parlavantzas, Nikos [3 ]
机构
[1] EDF R&D, 1 Ave Gen Gaule,BP 408, F-92141 Clamart, France
[2] INRIA, Campus Beaulieu, F-35042 Rennes, France
[3] IRISA, Campus Beaulieu, F-35042 Rennes, France
[4] KAUST, 4700 Thuwal, Jeddah 239556900, Saudi Arabia
关键词
Resource management; Cloud computing; Elastic scaling; Market mechanisms; Service Level Objective; HPC; COMPUTATIONAL ECONOMY; ALLOCATION; IMPLEMENTATION; TAXONOMY; WORKLOAD;
D O I
10.1016/j.jpdc.2016.10.003
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
High Performance Computing (HPC) clouds need to be efficiently shared between selfish tenants having applications with different resource requirements and Service Level Objectives (SLOB). The main difficulty relies on providing concurrent resource access to such tenants while maximizing the resource utilization. To overcome this challenge, we propose Merkat, a market-based SLO-driven cloud platform. Merkat relies on a market-based model specifically designed for on-demand fine-grain resource allocation to maximize resource utilization and it uses a combination of currency distribution and dynamic resource pricing to ensure proper resource distribution among tenants. To meet the tenant's SLO, Merkat uses autonomous controllers, which apply adaptation policies that: (i) dynamically tune the application's provisioned CPU and memory per virtual machine in contention periods, or (ii) dynamically change the number of virtual machines. Our evaluation with simulation and on the Grid'5000 testbed shows that Merkat provides flexible support for different application types and SLOB and good tenant satisfaction compared to existing centralized systems, while the infrastructure resource utilization is improved. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:85 / 102
页数:18
相关论文
共 50 条
  • [21] Application of a Probabilistic Market-based Approach in UAV Sensor & Perception Management
    Russ, Martin
    Stuetz, Peter
    [J]. 2013 16TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2013, : 676 - 683
  • [22] The Autonomous Recharging Problem: Formulation and a Market-based Solution
    Kannan, Balajee
    Marmol, Victor
    Bourne, Jaime
    Dias, M. Bernardine
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2013, : 3503 - 3510
  • [23] A taxonomy of market-based resource management systems for utility-driven cluster computing
    Yeo, Chee Shin
    Buyya, Rajkumar
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2006, 36 (13): : 1381 - 1419
  • [24] Market-Based Values [Market-Based Analyses]
    [J]. IEEE Consum. Electron. Mag., 4 (136-137):
  • [25] A market-based approach to marine sand resource management in the Pearl River estuary, China
    Zhao, Mingli
    Yang, Dewei
    Wang, Ping
    Shi, Ping
    [J]. OCEAN & COASTAL MANAGEMENT, 2015, 105 : 56 - 64
  • [26] Market-Based Resource Allocation for Service Overlay Networks
    Egashira, Ryota
    Suda, Tatsuya
    [J]. CAMAD: 2009 IEEE 14TH INTERNATIONAL WORKSHOP ON COMPUTER AIDED MODELING AND DESIGN OF COMMUNICATION LINKS AND NETWORKS, 2009, : 21 - 25
  • [27] Market-Based Cooperative Resource Allocation for Overlay Networks
    Egashira, Ryota
    Yahaya, Ariffin Datuk
    Suda, Tatsuya
    [J]. GLOBECOM 2009 - 2009 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE, VOLS 1-8, 2009, : 5943 - 5948
  • [28] Resource pricing under a market-based reservation protocol
    Lepler, JH
    Neuhoff, K
    [J]. FROM QOS PROVISIONING TO QOS CHARGING, PROCEEDINGS, 2002, 2511 : 303 - 314
  • [29] Market-based resource allocation for, content delivery in the Internet
    Erçetin, Ç
    Tassiulas, L
    [J]. IEEE TRANSACTIONS ON COMPUTERS, 2003, 52 (12) : 1573 - 1585
  • [30] Market-Based Resource Allocation Algorithms for IaaS Cloud
    Nayak, Sanjib Kumar
    Panda, Sanjaya Kumar
    Neha, Benazir
    Srichandan, Suresh Kumar
    [J]. 2018 FIFTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND GRID COMPUTING (IEEE PDGC), 2018, : 633 - 639