A Scheduling algorithm for Multi-Tenants Instance-Intensive Workflows

被引：8
作者：
Cui, Lizhen [1 ,2 ]
Zhang, Tiantian [1 ,2 ]
Xu, Guangquan [3 ]
Yuan, Dong [4 ]
机构：
[1] Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Peoples R China
[2] Shandong Prov Key Lab Software Engn, Jinan, Shandong, Peoples R China
[3] Tianjin Univ, Sch Comp Sci & Technol, Tianjin 300072, Peoples R China
[4] Swinburne Univ Technol, Fac Informat & Commun Technol, Melbourne, Vic, Australia
来源：
APPLIED MATHEMATICS & INFORMATION SCIENCES | 2013年 / 7卷
基金：
中国国家自然科学基金;
关键词：
Multi-tenants; Instance-intensive workflow; scheduling algorithm; SWINDEW; ASKALON;
D O I：
10.12785/amis/071L15
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
As a key service model in cloud computing, SaaS applications are becoming increasingly popular. Multi-tenancy is a key characteristics of SaaS applications. Business processes play a key role in SaaS applications because of the composability and reusability of software services. This paper focuses on multi-tenants instance-intensive workflows system, in which workflows have a large number of instances belonging to multiple tenants in a SaaS environment, and further proposes a scheduling algorithm for multi-tenants workflow instances. This algorithm improves the quality of service (QoS) for tenants and saves the execution cost of workflows. The simulation results demonstrate that the proposed algorithm guarantees the workflow execution conforming to the deadline set by tenants, and reduces the mean execution time for tenants in high priority whilst saves the execution cost for service providers.
引用
收藏
页码：99 / 105
页数：7
相关论文
共 26 条
  • [1] [Anonymous], 2009, CLOUDS BERKELEY VIEW
  • [2] [Anonymous], P 6 INT C PAR DISTR
  • [3] Bao P, 2012, APPL MATH INFORM SCI, V6, P99
  • [4] A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems
    Braun, TD
    Siegel, HJ
    Beck, N
    Bölöni, LL
    Maheswaran, M
    Reuther, AI
    Robertson, JP
    Theys, MD
    Yao, B
    Hensgen, D
    Freund, RF
    [J]. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2001, 61 (06) : 810 - 837
  • [5] Buyya R, 2004, GECON 2004, P19
  • [6] 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
  • [7] Chong F., 2006, ARCHITECTURE STRATEG
  • [8] De PK, 2011, APPL MATH INFORM SCI, V5, P253
  • [9] ASKALON: a tool set for cluster and Grid computing
    Fahringer, T
    Jugravu, A
    Pllana, S
    Prodan, R
    Seragiotto, CJ
    Truong, HL
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2005, 17 (2-4) : 143 - 169
  • [10] GREEDY RANDOMIZED ADAPTIVE SEARCH PROCEDURES
    FEO, TA
    RESENDE, MGC
    [J]. JOURNAL OF GLOBAL OPTIMIZATION, 1995, 6 (02) : 109 - 133
123