›› 2017, Vol. 32 ›› Issue (2): 250-257.doi: 10.1007/s11390-017-1719-x

Special Issue: Computer Architecture and Systems; Software Systems

• Special Section on MOST Cloud and Big Data • Previous Articles     Next Articles

Experience Availability: Tail-Latency Oriented Availability in Software-Defined Cloud Computing

Bin-Lei Cai1, Student Member, CCF, Rong-Qi Zhang1, Xiao-Bo Zhou1,*, Member, CCF, ACM, IEEE, Lai-Ping Zhao2, Member, CCF, ACM, IEEE, Ke-Qiu Li1, Senior Member, CCF, IEEE, Member, ACM   

  1. 1 Tianjin Key Laboratory of Advanced Networking, School of Computer Science and Technology, Tianjin University Tianjin 300350, China;
    2 School of Computer Software, Tianjin University, Tianjin 300350, China
  • Received:2016-12-11 Revised:2017-02-08 Online:2017-03-05 Published:2017-03-05
  • Contact: Xiao-Bo Zhou E-mail:xiaobo.zhou@tju.edu.cn
  • About author:Bin-Lei Cai received his Master's degree in computer science from the School of Information Science and Engineering of Yanshan University, Qinhuangdao, in 2011. Currently, he is pursuing his Ph.D. degree in the School of Computer Science and Technology, Tianjin University, Tianjin. His research interests include cloud computing, performance evaluation and availability modeling.
  • Supported by:

    This work is supported by the National Key Research and Development Program of China under Grant No. 2016YFB1000205, the National Natural Science Foundation of China under Grant No. 61402325, and the Tianjin City Application Foundation and Cutting-Edge Technology Research Program under Grant No. 14JCQNJC00500.

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Resource sharing, multi-tenant interference and bursty workloads in cloud computing lead to high tail-latency that severely affects user quality of experience (QoE), where response latency is a critical factor. A lot of research efforts are dedicated to reducing high tail-latency and improving user QoE, such as software-defined cloud computing (SDC). However, the traditional availability analysis of cloud computing captures the pure failure-repair behavior with user QoE ignored. In this paper, we propose a conceptual framework, experience availability, to properly assess the effectiveness of SDC while taking into account both availability and response latency simultaneously. We review the related work on availability models and methods of cloud systems, and discuss open problems for evaluating experience availability in SDC. We also show some of our preliminary results to demonstrate the feasibility of our ideas.

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