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王康瑾  等:在离线混部作业调度与资源管理技术研究综述                                                      3119


         [89]    Sriraman A, Dhanotia A, Wenisch TF. Softsku: Optimizing server architectures for microservice diversity@ scale. In: Proc. of the
             46th Int’l Symp. on Computer Architecture. 2019. 513–526.
         [90]    Gan Y, Zhang Y, Cheng D, et al. An open-source benchmark suite for microservices and their hardware-software implications for
             cloud &  edge systems. In: Proc. of  the 24th Int’l  Conf. on Architectural Support for Programming  Languages and  Operating
             Systems. ACM, 2019. 3–18.
         [91]    Dean J, Barroso LA. The tail at scale. Communications of the ACM, 2013,56(2):74–80.
         [92]    Memcached. https://www.memcached.org/
         [93]    Redis. https://redis.io/
         [94]    Yang Y, Wan L, Gu J, Li Y. Transparently capturing execution path of service/job request processing. In: Proc. of the 16th Int’l
             Conf. on Service Oriented Computing (ICSOC 2018). 2018. 12–15.
         [95]    Wulf WA, McKee SA. Hitting the memory wall: Implications of the obvious. ACM SIGARCH Computer Architecture News, 1995,
             23(1):20–24.
         [96]    Calheiros RN, Ranjan R, De Rose CAF,  et al. CloudSim: A novel framework for modeling and simulation of cloud computing
             infrastructures and services. Computer Science, 2009.
         [97]    Chen W, Deelman E. WorkflowSim: A toolkit for simulating scientific workflows in distributed environments. In: Proc. of the IEEE
             Int’l Conf. on E-science. 2013.
         [98]    Bux M, Leser U. DynamicCloudSim: Simulating heterogeneity in computational clouds. In: Proc. of the ACM SIGMOD Workshop
             on Scalable Workflow Execution Engines & Technologies. 2013.
         [99]    Wunderlich RE, Wenisch TF, Falsafi B, et al. SMARTS: Accelerating microarchitecture simulation via rigorous statistical sampling.
             In: Proc. of the 30th Annual Int’l Symp. on Computer Architecture. 2003. 84–97.
        [100]    Zhang FX, Zhang LB, Hu WW. Sim-Godson: A godson processor simulator based on SimpleScalar. Chinese Journal of Computers,
             2007,30(1):68 (in Chinese with English abstract).
        [101]    Sanchez D, Kozyrakis C. ZSim: Fast and accurate microarchitectural simulation of  thousand-core  systems. ACM SIGARCH
             Computer Architecture News, 2013,41(3):475–486.
        [102]    Binkert N, Beckmann B, Black G, et al. The Gem5 simulator. ACM SIGARCH Computer Architecture News, 2011,39(2):1–7.
        [103]    Zhang Y, Gan Y, Delimitrou C. uqSim: Scalable and validated simulation of cloud microservices. arXiv Preprint arXiv: 1911.02122,
             2019.

         附中文参考文献:
          [7]  杜小勇,卢卫,张峰.大数据管理系统的历史、现状与未来.软件学报,2019,30(1):127–141. http://www.jos.org.cn/1000-9825/5644.
             htm [doi: 10.13328/j.cnki.jos.005644]
         [32]  赵家程,崔慧敏,冯晓兵.基于统计学习分析多核间性能干扰.软件学报,2013,24(11):2558−2570. http://www.jos.org.cn/1000-9825/
             4482.htm [doi: 10.3724/SP.J.1001.2013.04482]
         [47]  李青,李勇,涂碧波,等.QoS 保证的数据中心动态资源供应方法.计算机学报,2014,37(12):2395−2407.
        [100]  张福新,章隆兵,胡伟武.基于 SimpleScalar 的龙芯 CPU 模拟器 Sim-Godson.计算机学报,2007,30(1):70–75.




                       王康瑾(1993-),男,博士,主要研究领域为                      李影(1975-),女,博士,教授,博士生导师,
                       云计算系统,在离线混部系统.                               CCF 高级会员,主要研究领域为分布式计
                                                                    算,可信计算.



                       贾统(1993-),男,博士,主要研究领域为
                       分布式系统,智能运维.
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