FSCRank: A Failure-Sensitive Structure-Based Component Ranking Approach for Cloud Applications

Na WU  Decheng ZUO  Zhan ZHANG  Peng ZHOU  Yan ZHAO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E102-D   No.2   pp.307-318
Publication Date: 2019/02/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDP7197
Type of Manuscript: PAPER
Category: Dependable Computing
Keyword: 
component ranking,  failure impact,  application structure,  buffer node,  availability improvement,  

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Summary: 
Cloud computing has attracted a growing number of enterprises to move their business to the cloud because of the associated operational and cost benefits. Improving availability is one of the major concerns of cloud application owners because modern applications generally comprise a large number of components and failures are common at scale. Fault tolerance enables an application to continue operating properly when failure occurs, but fault tolerance strategy is typically employed for the most important components because of financial concerns. Therefore, identifying important components has become a critical research issue. To address this problem, we propose a failure-sensitive structure-based component ranking approach (FSCRank), which integrates component failure impact and application structure information into component importance evaluation. An iterative ranking algorithm is developed according to the structural characteristics of cloud applications. The experimental results show that FSCRank outperforms the other two structure-based ranking algorithms for cloud applications. In addition, factors that affect application availability optimization are analyzed and summarized. The experimental results suggest that the availability of cloud applications can be greatly improved by implementing fault tolerance strategy for the important components identified by FSCRank.