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视频点播系统的软件老化估计和预测 被引量:6

Software Aging Pattern Analysis of the Video on Demand System
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摘要 针对视频点播系统,研究其软件老化模式.对系统资源和视频点播服务器的实时参数,采用Mann-Kendall方法来检测老化趋势以判断系统是否存在软件老化现象,并采用Sen的斜率估计方法来估计老化衰退速率;提出了基于径向基网络的软件老化预测模型,对老化趋势进行预测,并采用主成分分析方法来减少径向基网络的复杂度以提高效率.实验结果表明:视频点播系统中存在软件老化现象;基于径向基网络的软件老化预测模型预测效果优于时间序列模型.基于提出方法以及对视频点播系统的老化分析,可为进一步研究相应的软件再生策略提供理论依据. Video-on-demand (VOD) system is an essential and widely used multimedia application. The importance of software reliability and availability has been well recognized and demanded. The phenomenon of software aging refers to the exhaustion of operating system resource, fragmentation and accumulation of errors, which results in progressive performance degradation or transient failures or even crashes of applications. The software aging patterns of a real VOD system are investigated. Firstly, the data on several system resource usage and application server are collected. Then, the Mann-Kendall test method is adopted to detect aging trend, and Sen's slope estimator is applied to estimate the aging degree in the data sets. Finally, radial basis function (RBF) network models are constructed to model the extracted data series of systematic parameters and to predict software aging of the VOD system. In order to reduce the complexity of RBF networks and to improve its efficiency, principal component analysis (PCA) is used to reduce the dimensionality of input variables of the networks. The experimental results show that the software aging exists in the VOD system and the software aging prediction model based on RBF network is superior to the time series models in the aspects of prediction precision. Based on the models employed here, software rejuvenation policies can be triggered by actual measurements.
出处 《计算机研究与发展》 EI CSCD 北大核心 2011年第11期2139-2146,共8页 Journal of Computer Research and Development
基金 国家自然科学基金重点项目(60933003) 国家“八六三”高技术研究发展计划基金项目(2009AA01Z116) 陕西省科学技术研究发展计划基金项目(2008kw-02) IBM合作项目(JLP200906008-1) 高效能服务器和存储技术国家重点实验室开放基金项目(2009HSSA09)
关键词 软件老化 老化预测 老化估计 视频点播 软件可靠性 software aging aging prediction aging estimation VOD software reliability
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参考文献21

  • 1Paulson L D. Computer system, heal thyself [J]. IEEE Computer, 2002, 35(8): 20-22.
  • 2吴艾,刘心松,符青云,刘克剑.DPVoD:基于P2P的视频点播体系结构[J].计算机研究与发展,2008,45(2):269-277. 被引量:4
  • 3Papazoglou P M, Karras D A, Papademetriou R C. Improved integral channel allocation algorithms in cellular communication systems enabling multimedia QoS services [J]. WSEAS Trans on Communications, 2008, 7(10): 1014-1023.
  • 4Rubino G, Varela M, Bonnin J M. Controlling multimedia QoS in the future home network using the PSQA metric [J]. The Computer Journal, 2006, 49(2) : 137-155.
  • 5Huang Y, Kintala C, Kolettis N, et al. Software rejuvenation: Analysis, module and applications [C] //Proc of the 25th Int Syrup on Fault Tolerant Computing. Los Alamitos, CA: IEEE Computer Society, 1995:381-390.
  • 6Marshall E. Fatal error: How Pariot overlooked a scud[J]. Science, 199Z, 255(5050): 1347-1347.
  • 7Garg S, et al. A methodology for detection and estimation of software aging [C]//Proc of 9th Int Symp on Software Reliability Engineering. Los Alamitos, CA: IEEE Computer Society, 1998:283-292.
  • 8Cotroneo D, Orlando S, Russo S. Characterizing aging phenomena of the java virtual machine [C] //Proe of IEEE SRDS'09. Los Alamitos, CA: IEEE Computer Society, 2007:127-136.
  • 9Grottke M, Li Lei, Vaidyanathan K, et al. Analysis of software aging in a Web server [J]. IEEE Trans on Reliability, 2006, 55(3): 411-420.
  • 10Silva L, Madeira H, Silva J G. Software aging and rejuvenation in a soap-based server[C] //Proe of IEEE NCA06. Los Alamitos, CA: IEEE Computer Society, 2006: 56-65.

二级参考文献25

  • 1贺小箭,尤晋元,薛广涛.基于P2P网格的视频点播自适应性研究[J].计算机研究与发展,2004,41(12):2200-2205. 被引量:7
  • 2刘亚杰,窦文华.一种P2P环境下的VoD流媒体服务体系[J].软件学报,2006,17(4):876-884. 被引量:29
  • 3刘威,Chun Tung Chou,程文青,杜旭.交互式流媒体代理缓存[J].计算机研究与发展,2006,43(4):594-600. 被引量:5
  • 4Huang Y, Kintala C, Kolettis N, Fulton N. Software rejuvenation: Analysis, module and applieations//Proceedings of the IEEE International Symposium on Fault Tolerant Computing. Canada, 1995: 381-390
  • 5Avritzer A, Weyuke J. Monitoring smoothly degrading systems for increased dependability. Empirical Software Engineering, 1997, 2(1): 59-77
  • 6Dohi T, Goseva-Popstojanova K, Trivedi K S. Statistical non-parametric algorithms to estimate the optimal software rejuvenation schedule//Proceedings of the Pacific Rim International Symposium on Dependable Computing (PRDC 2000). Los Angeles, USA, 2000:77-84
  • 7Pfening A, Garg S, Puliafito A, Telek M, Trivedi K S. Optimal software rejuvenation for toleration software failures// Proceedings of the 18th International Symposium on Performance Evluation. Lausanne, Switzerland, 1996:491-506
  • 8Xie Wei, Hong Yi-Guang, Trivedi Kishor. Analysis of a two-level software rejuvenation policy. Reliability Engineering and System Safety, 2005, 87(1) : 13-22
  • 9Castelli Vet al. Proactive management of software aging. IBM Journal of Research & Development, 2001, 45(2): 311-332
  • 10Garg S, Huang Y, Kintala C, Trivedi K S. Time and load based software rejuvenation: Policy, evaluation and optimality//Proceedings of the 1st Fault Tolerance Symposium, FTS-95. Madras, India, 1995: 22-25

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同被引文献41

  • 1肖艳文,王金宝,李亚平,高宏.云计算系统中能量有效的数据摆放算法和节点调度策略[J].计算机研究与发展,2013,50(S1):342-351. 被引量:9
  • 2王雅娣,曹长修,任江洪,叶仲泉.模糊RBF神经网络在专家系统知识库建立中的应用[J].计算机工程,2005,31(3):175-177. 被引量:13
  • 3HAYKINS.Neuralnetworks[M].叶世伟,史忠植,译.北京,机械工业出版社,2004.
  • 4GALUSHKIN A I. Neural networks theory[ M]. Berlin: Springer- Verlag, 2010.
  • 5PARK H S, PEDRYCZ W, CHUNG Y D, et al. Modeling of the charging characteristic of linear-type superconducting power supply using granular-based radial basis function neural networks [ J]. Ex- pert Systems with Applications, 2012, 39(1) : 1021 - 1039.
  • 6MITCHELL T M. Machine learning[ M]. New York: McGraw-Hill, 1997: 23.
  • 7王耀南,张东波,黄辉先,易灵芝.粗糙集意义下的一种RBF神经网络设计方法[J].控制与决策,2007,22(10):1091-1096. 被引量:7
  • 8Huang Y, Kintala C, Kolettis N, et al. Software rejuve- nation: Analysis, module and applications. In: Proceed- ings of the Twenty-Fifth International Symposium on Fault-Tolerant Computing, IEEE, Pasadena, USA, 1995. 381-390.
  • 9Kourai K, Chiba S. A fast rejuvenation technique for server consolidation with virtual machines. In: Proceed- ings of the 37th Annual IEEE/IFIP International Confer- ence on Dependable Systems and Networks, Edinburgh, UK, 2007. 245-255.
  • 10Araujo J, Matos R, Maciel P, et al. Experimental evalu- ation of software aging effects on the eucalyptus cloud computing infrastructure. In. Proceedings of the Middle- ware 2011 Industry Track Workshop. ACM, Lisbon, Por- tugal, 2011. 4.

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