? 体验可用性:面向尾延迟的软件定义的云计算的可用性
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Journal of Computer Science and Technology 2017, Vol. 32 Issue (2) :250-257    DOI: 10.1007/s11390-017-1719-x
Special Section on MOST Cloud and Big Data << Previous Articles | Next Articles >>
体验可用性:面向尾延迟的软件定义的云计算的可用性
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 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
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 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

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摘要 当前云计算的资源无序共享、多租户间的干扰以及突发的负载导致长尾延迟现象严重,从而严重影响用户体验。大量研究工作都致力于降低长尾延迟来提高用户体验,例如软件定义的云计算。尾延迟是影响软件定义的云计算的可用性的重要因素,然而传统的云计算的可用性分析仅考虑系统的失效/修复行为而忽略了用户体验。为了准确地评估软件定义的云计算的可用性,本文提出体验可用性这一概念以同时度量系统的失效/修复行为和尾延迟响应,并分析现有云计算的可用性建模与分析方法。在此基础上,进一步探讨对软件定义的云计算进行体验可用性评估存在的挑战。最后,通过初步的实验证实,利用体验可用性能够有效地度量软件定义的云计算的可用性。
关键词云计算   软件定义的云计算   可用性   尾延迟     
Abstract: 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.
Keywordscloud computing   software-defined cloud computing (SDC)   availability   tail-latency     
Received 2016-12-11;
本文基金:

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.

通讯作者: Xiao-Bo Zhou     Email: 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.
引用本文:   
Bin-Lei Cai, Rong-Qi Zhang, Xiao-Bo Zhou, Lai-Ping Zhao, Ke-Qiu Li.体验可用性:面向尾延迟的软件定义的云计算的可用性[J]  Journal of Computer Science and Technology , 2017,V32(2): 250-257
Bin-Lei Cai, Rong-Qi Zhang, Xiao-Bo Zhou, Lai-Ping Zhao, Ke-Qiu Li.Experience Availability: Tail-Latency Oriented Availability in Software-Defined Cloud Computing[J]  Journal of Computer Science and Technology, 2017,V32(2): 250-257
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