The arrangement of file systems and volume management/RAID systems, together commonly referred to as the storage stack, has remained the same for several decades, despite significant changes in hardware, software and usage scenarios. In this paper, we evaluate the traditional storage stack along three dimensions: reliability, heterogeneity and flexibility. We highlight several major problems with the traditional stack. We then present Loris, our redesign of the storage stack, and we evaluate several aspects of Loris.
{"title":"Loris - A Dependable, Modular File-Based Storage Stack","authors":"Raja Appuswamy, D. V. Moolenbroek, A. Tanenbaum","doi":"10.1109/PRDC.2010.41","DOIUrl":"https://doi.org/10.1109/PRDC.2010.41","url":null,"abstract":"The arrangement of file systems and volume management/RAID systems, together commonly referred to as the storage stack, has remained the same for several decades, despite significant changes in hardware, software and usage scenarios. In this paper, we evaluate the traditional storage stack along three dimensions: reliability, heterogeneity and flexibility. We highlight several major problems with the traditional stack. We then present Loris, our redesign of the storage stack, and we evaluate several aspects of Loris.","PeriodicalId":382974,"journal":{"name":"2010 IEEE 16th Pacific Rim International Symposium on Dependable Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125674182","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}
Predicting failures at runtime is one of the most promising techniques to increase the availability of computer systems. However, failure prediction algorithms are still far from providing satisfactory results. In particular, the identification of the variables that show symptoms of incoming failures is a difficult problem. In this paper we propose an approach for identifying the most adequate variables for failure prediction. Realistic software faults are injected to accelerate the occurrence of system failures and thus generate a large amount of failure related data that is used to select, among hundreds of system variables, a small set that exhibits a clear correlation with failures. The proposed approach was experimentally evaluated using two configurations based on Windows XP. Results show that the proposed approach is quite effective and easy to use and that the injection of software faults is a powerful tool for improving the state of the art on failure prediction.
{"title":"Towards Identifying the Best Variables for Failure Prediction Using Injection of Realistic Software Faults","authors":"Ivano Irrera, J. Durães, M. Vieira, H. Madeira","doi":"10.1109/PRDC.2010.51","DOIUrl":"https://doi.org/10.1109/PRDC.2010.51","url":null,"abstract":"Predicting failures at runtime is one of the most promising techniques to increase the availability of computer systems. However, failure prediction algorithms are still far from providing satisfactory results. In particular, the identification of the variables that show symptoms of incoming failures is a difficult problem. In this paper we propose an approach for identifying the most adequate variables for failure prediction. Realistic software faults are injected to accelerate the occurrence of system failures and thus generate a large amount of failure related data that is used to select, among hundreds of system variables, a small set that exhibits a clear correlation with failures. The proposed approach was experimentally evaluated using two configurations based on Windows XP. Results show that the proposed approach is quite effective and easy to use and that the injection of software faults is a powerful tool for improving the state of the art on failure prediction.","PeriodicalId":382974,"journal":{"name":"2010 IEEE 16th Pacific Rim International Symposium on Dependable Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124933858","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}
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