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IJSTR >> Volume 6 - Issue 9, September 2017 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Failure Prediction And Detection In Cloud Datacenters

[Full Text]



Purvil Bambharolia, Prajeet Bhavsar, Vivek Prasad



Cloud computing; failure prediction; failure detection; cloud datacenters; probability and statistics; Bayesian probability; machine learning



Cloud computing is a novel technology in the field of distributed computing. Usage of Cloud computing is increasing rapidly day by day. In order to serve the customers and businesses satisfactorily, fault occurring in datacenters and servers must be detected and predicted efficiently in order to launch mechanisms to tolerate the failures occurred. Failure in one of the hosted datacenters may propagate to other datacenters and make the situation worse. In order to prevent such situations, one can predict a failure proliferating throughout the cloud computing system and launch mechanisms to deal with it proactively. One of the ways to predict failures is to train a machine to predict failure on the basis of messages or logs passed between various components of the cloud. In the training session, the machine can identify certain message patterns relating to failure of data centers. Later on, the machine can be used to check whether a certain group of message logs follow such patterns or not. Moreover, each cloud server can be defined by a state which indicates whether the cloud is running properly or is facing some failure. Parameters such as CPU usage, memory usage etc. can be maintained for each of the servers. Using this parameters, we can add a layer of detection where in we develop a decision tree based on these parameters which can classify whether the passed in parameters to the decision tree indicate failure state or proper state.



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