Truthful Strategy and Resource Integration for Multi-tenant Data Center Demand Response

被引:5
|
作者
Wang, Youshi [1 ,4 ]
Zhang, Fa [2 ]
Liu, Zhiyong [1 ,3 ]
机构
[1] Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing, Peoples R China
[2] Chinese Acad Sci, ICT, Key Lab Intelligent Informat Proc, Beijing, Peoples R China
[3] Chinese Acad Sci, ICT, State Key Lab Comp Architecture, Beijing, Peoples R China
[4] Univ Chinese Acad Sci, Beijing, Peoples R China
来源
FRONTIERS IN ALGORITHMICS (FAW 2015) | 2015年 / 9130卷
关键词
Colocation; Emergency demand response; Uncoordinated relationship; Truthful strategy design; Algorithm analysis;
D O I
10.1007/978-3-319-19647-3_24
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Data centers' demand response (DR) program has been paid more and more attention recently. As an important component of data centers, multi-tenant data centers (also called "colocation") play a significant role in the demand response, especially in the emergency demand response (EDR). In this paper, we focus on how the colocation can perform better in the EDR program. We formulate the "uncoordinated relationship" in the colocation which is the key problem affecting energy efficiency, and propose a reward system to motivate tenants to join the EDR program, and a truthful strategy is developed to ensure the authenticity of tenants' information. For achieving the overall coordination, we integrate tenants' resources to increase the colocation's resource utilization and optimize the whole colocation's energy efficiency, then devise two algorithms to solve the actual resource migration and integration problem. We analyze the complexity of allocation model and two algorithms. Experimental results show that our solution is practical and efficient.
引用
收藏
页码:259 / 270
页数:12
相关论文
共 50 条
  • [31] Data Placement for Multi-Tenant Data Federation on the Cloud
    Liu, Ji
    Mo, Lei
    Yang, Sijia
    Zhou, Jingbo
    Ji, Shilei
    Xiong, Haoyi
    Dou, Dejing
    IEEE TRANSACTIONS ON CLOUD COMPUTING, 2023, 11 (02) : 1414 - 1429
  • [33] Data isolation in multi-tenant SaaS environment
    Gupta, Keshav
    Kumar, Sandeep
    Agnihotri, Ojaswi
    2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND AUTOMATION (ICCCA), 2016, : 1290 - 1292
  • [34] A Multi-Tenant Resource Management System for Multi-FPGA Systems
    Yamakura, Miho
    Takano, Ryousei
    Ben Ahmed, Akram
    Sugaya, Midori
    Amano, Hideharu
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2021, E104D (12): : 2078 - 2088
  • [35] Bandwidth Guarantee under Demand Uncertainty in Multi-tenant Clouds
    Yu, Lei
    Shen, Haiying
    2014 IEEE 34TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2014), 2014, : 258 - 267
  • [36] A SDN for Multi-tenant Data Center Based on IPv6 Transition Method
    Sheng Maojia
    Bao Congxiao
    Li Xing
    2016 IEEE INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC), 2016, : 190 - 195
  • [37] Virtual Network Allocation for Fault Tolerance with Bandwidth Efficiency in a Multi-Tenant Data Center
    Ogawa, Yukio
    Hasegawa, Go
    Murata, Masayuki
    2014 IEEE 6TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), 2014, : 555 - 562
  • [38] Toward Performance Optimization with CPU Offloading for Virtualized Multi-Tenant Data Center Networks
    Lin, An-Dee
    Franke, Hubertus
    Li, Chung-Sheng
    Liao, Wanjiun
    IEEE NETWORK, 2016, 30 (03): : 59 - 63
  • [39] Scheduling multi-tenant cloud workflow tasks with resource reliability
    Xiaoping LI
    Dongyuan PAN
    Yadi WANG
    Rubén RUIZ
    ScienceChina(InformationSciences), 2022, 65 (09) : 127 - 144
  • [40] A Configurable Resource Allocation for Multi-tenant Process Development in the Cloud
    Hachicha, Emna
    Assy, Nour
    Gaaloul, Walid
    Mendling, Jan
    ADVANCED INFORMATION SYSTEMS ENGINEERING (CAISE 2016), 2016, 9694 : 558 - 574