2008 International Conference on Autonomic Computing最新文献_第3页

Automating ITSM Incident Management Process 自动化ITSM事件管理过程

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.22

Rajeev Gupta, K. H. Prasad, M. Mohania

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引用次数: 51

Just-in-Time Server Provisioning Using Virtual Machine Standby and Request Prediction 使用虚拟机备用和请求预测的即时服务器配置

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.13

F. Machida, M. Kawato, Y. Maeno

引用次数: 8

Semantic-Driven Model Composition for Accurate Anomaly Diagnosis 面向准确异常诊断的语义驱动模型组合

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.33

Saeed Ghanbari, C. Amza

{"title":"Semantic-Driven Model Composition for Accurate Anomaly Diagnosis","authors":"Saeed Ghanbari, C. Amza","doi":"10.1109/ICAC.2008.33","DOIUrl":"https://doi.org/10.1109/ICAC.2008.33","url":null,"abstract":"In this paper, we introduce a semantic-driven approach to system modeling for improving the accuracy of anomaly diagnosis. Our framework composes heterogeneous families of models, including generic statistical models, and resource-specific models into a belief network, i.e., Bayesian network. Given a set of models which sense the behavior of various system components, the key idea is to incorporate expert knowledge about the system structure and dependencies within this structure, as meta-correlations across components and models. Our approach is flexible, easily extensible and does not put undue burden on the system administrator. Expert beliefs about the system hierarchy, relationships and known problems can guide learning, but do not need to be fully specified. The system dynamically evolves its beliefs about anomalies over time. We evaluate our prototype implementation on a dynamic content site running the TPC-W industry-standard e- commerce benchmark. We sketch a system structure and train our belief network using automatic fault injection. We demonstrate that our technique provides accurate problem diagnosis in cases of single and multiple faults. We also show that our semantic-driven modeling approach effectively finds the component containing the root cause of injected anomalies, and avoids false alarms for normal changes in environment or workload.","PeriodicalId":436716,"journal":{"name":"2008 International Conference on Autonomic Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122127647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 27

Dealing with Quality Tradeoffs during Service Selection 在服务选择过程中处理质量权衡

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.8

C. Herssens, Ivan Jureta, Stéphane Faulkner

引用次数: 26