FTCRank: Ranking Components for Building Highly Reliable Cloud Applications

With the increasing popularity of cloud computing[2], building highly reliable applications on cloud is very important. However, it's hard to give an optimal solution for large-scale cloud applications. In order to provide an effective solution on this research problem, we propose a component ranking approach named as FTCRank for applying fault-tolerant strategies to the significant components. FTCRank considers not only structure information but also component characteristics to obtain the result. Experiments show that FTCRank achieves better results than other existing algorithms in Top-K fault-tolerant cloud tasks.

[1]  Zibin Zheng,et al.  Titan: a system for effective web service discovery , 2012, WWW.

[2]  Zibin Zheng,et al.  An Enhanced QoS Prediction Approach for Service Selection , 2011, 2011 IEEE International Conference on Services Computing.

[3]  Brian Randell,et al.  The Evolution of the Recovery Block Concept , 1994 .

[4]  Liang Chen,et al.  MapReduce Based Skyline Services Selection for QoS-aware Composition , 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum.

[5]  Brian Hayes,et al.  What Is Cloud Computing? , 2019, Cloud Technologies.

[6]  Rajkumar Buyya Cloud computing: The next revolution in information technology , 2010, 2010 First International Conference On Parallel, Distributed and Grid Computing (PDGC 2010).

[7]  Vladimir Stantchev,et al.  A survey on IT-governance aspects of cloud computing , 2011, Int. J. Web Grid Serv..

[8]  Zibin Zheng,et al.  FTCloud: A Component Ranking Framework for Fault-Tolerant Cloud Applications , 2010, 2010 IEEE 21st International Symposium on Software Reliability Engineering.

[9]  Stan Lipovetsky,et al.  Pareto 80/20 law: derivation via random partitioning , 2009 .

[10]  Zibin Zheng,et al.  Component Ranking for Fault-Tolerant Cloud Applications , 2012, IEEE Transactions on Services Computing.

[11]  Algirdas A. Avi The Methodology of N-Version Programming , 1995 .