期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

云计算环境下分布式缓存技术的现状与挑战 被引量：75

Progress and Challenges of Distributed Caching Techniques in Cloud Computing
下载PDF
导出
摘要 作为云平台提升应用性能的一种重要手段,分布式缓存技术近年来受到了工业界和学术界的广泛关注.从云计算与分布式缓存技术的结合入手,分析介绍了分布式缓存的特性、典型应用场景、发展阶段、相关标准规范以及推动缓存技术发展的若干关键要素.为系统地了解分布式缓存技术的现状和不足,建立了一个云环境下分布式缓存技术的分析框架——DctAF.该框架从分析云计算的特点和缓存技术的边界出发,涵盖6个分析维度.基于DctAF框架,对当前缓存技术进行总结和分析,并对典型系统进行比较.在此基础上,深入阐述了云环境下分布式缓存系统面临的挑战;围绕上述挑战,分析和比较了已有的研究工作. As an important application of acceleration in the cloud, the distributed caching technology has received considerable attention in industry and academia. This paper starts with a discussion on the combination of cloud computing and distributed caching technology, giving an analysis of its characteristics, typical application scenarios, stages of development, standards, and several key elements, which have promoted its development. In order to systematically know the state of art progress and weak points of the distributed caching technology, the paper builds a multi-dimensional framework, DctAF. This framework is constituted of 6 dimensions through analyzing the characteristics of cloud computing and boundary of the caching techniques. Based on DctAF, current techniques have been analyzed and summarized; comparisons among several influential products have also been made. Finally, the paper describes and highlights the several challenges that the cache system faces and examines the current research through in-depth analysis and comparison.
作者 秦秀磊 张文博 魏峻 王伟 钟华 黄涛
机构地区 中国科学院软件研究所软件工程技术中心 中国科学院软件研究所计算机科学国家重点实验室 中国科学院研究生院
出处 《软件学报》 EI CSCD 北大核心 2013年第1期50-66,共17页 Journal of Software
基金 国家重点基础研究发展计划(973)(2009CB320704) 国家自然科学基金(61173003 61100068) 国家高技术研究发展计划(863)(2012AA011204) 国家科技支撑计划(2011BAH15B03)
关键词 分析框架 云计算 分布式缓存 analysis framework cloud computing distributed cache
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献62

  • 1Caching data sources. Oracle. 2011. http://download.oracle.com/docs/cd/E24290_O1/coh.371/e22837/cache_rtwtwbra.htm# CFHEDIGA.
  • 2Peralta P. Successfully scaling Java applications in spring. Oracle Corp. 2007. http://www.nejug.org/events/download?f=41.
  • 3Brewer EA. Towards robust distributed systems. In: Proc. of the 19th Annual ACM Symp. on Principles of Distributed Computing (PODC 2000). 2000. [doi: 10.1145/343477.343502].
  • 4Lu C, Alvarez GA, Wilkes J. Aqueduct: Online data migration with performance guarantees. In: Proc. of the USENIX Conf. on File and Storage Technologies (FAST 2002). Monterey: USENIX Association, 2002. 219-230.
  • 5Multitenancy. Wikipedia. 2008. http://en.wikipedia.org/wiki/Multitenancy.
  • 6Ari 1, Amer A, Miller EL, Brandt SA, Long DE. Who is more adaptive? ACME: Adaptive caching using multiple experts. In: Proc. of the Workshop on Distributed Data and Structures (WDAS 2002). Paris, 2002. 143-158.
  • 7Megiddo N, Modha DS. ARC: A self-tuning, low overhead replacement cache. In: Proc. of the 2nd USENIX Conf. on File and Storage Technologies (FAST 2003). San Francisco: USENIX Association, 2003. 115-130.
  • 8NCache: Caching topologies. 2008. http://www.alachisoft.com/ncache/caching-topology.html.
  • 9Earls A. Distributed data grids: Foundation for future cloud computing? 2010. http://searchsoa.techtarget.com/news/1518647/Data- Grids-Foundation-for- future-cloud-computing.
  • 10Prabhakar R, Srikantaiah S, Kandemir M, Patrick CM, Kandemir M. Adaptive multi-level cache allocation in distributed storage architectures. In: Proc. of the 24th ACM Int'l Conf. of Supercomputing (ICS 2010). 2010. 211-221. [doi: 10.1145/1810085. 1810115].

二级参考文献43

  • 1Sims K. IBM introduces ready-to-use cloud computing collaboration services get clients started with cloud computing. 2007. http://www-03.ibm.com/press/us/en/pressrelease/22613.wss
  • 2Boss G, Malladi P, Quan D, Legregni L, Hall H. Cloud computing. IBM White Paper, 2007. http://download.boulder.ibm.com/ ibmdl/pub/software/dw/wes/hipods/Cloud_computing_wp_final_8Oct.pdf
  • 3Zhang YX, Zhou YZ. 4VP+: A novel meta OS approach for streaming programs in ubiquitous computing. In: Proc. of IEEE the 21st Int'l Conf. on Advanced Information Networking and Applications (AINA 2007). Los Alamitos: IEEE Computer Society, 2007. 394-403.
  • 4Zhang YX, Zhou YZ. Transparent Computing: A new paradigm for pervasive computing. In: Ma JH, Jin H, Yang LT, Tsai JJP, eds. Proc. of the 3rd Int'l Conf. on Ubiquitous Intelligence and Computing (UIC 2006). Berlin, Heidelberg: Springer-Verlag, 2006. 1-11.
  • 5Barroso LA, Dean J, Holzle U. Web search for a planet: The Google cluster architecture. IEEE Micro, 2003,23(2):22-28.
  • 6Brin S, Page L. The anatomy of a large-scale hypertextual Web search engine. Computer Networks, 1998,30(1-7): 107-117.
  • 7Ghemawat S, Gobioff H, Leung ST. The Google file system. In: Proc. of the 19th ACM Symp. on Operating Systems Principles. New York: ACM Press, 2003.29-43.
  • 8Dean J, Ghemawat S. MapReduce: Simplified data processing on large clusters. In: Proc. of the 6th Symp. on Operating System Design and Implementation. Berkeley: USENIX Association, 2004. 137-150.
  • 9Burrows M. The chubby lock service for loosely-coupled distributed systems. In: Proc. of the 7th USENIX Symp. on Operating Systems Design and Implementation. Berkeley: USENIX Association, 2006. 335-350.
  • 10Chang F, Dean J, Ghemawat S, Hsieh WC, Wallach DA, Burrows M, Chandra T, Fikes A, Gruber RE. Bigtable: A distributed storage system for structured data. In: Proc. of the 7th USENIX Symp. on Operating Systems Design and Implementation. Berkeley: USENIX Association, 2006. 205-218.

共引文献1351

同被引文献620

引证文献75

二级引证文献296

软件学报
2013年 第1期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部