DocumentCode
3287852
Title
FTAB: Fault tolerance approach by using HMM with BAUM-WELCH algorithm in MCC
Author
Patel, Pragati ; Prakash, V.
Author_Institution
Dept. of Comput. Sci. & Eng., SVITS, Indore, India
fYear
2013
fDate
26-28 July 2013
Firstpage
1
Lastpage
4
Abstract
Fault tolerance in mobile cloud computing is highly important aspect, even more than a conventional cloud computing because of the mobile nature of devices i.e. mobility. Mobile cloud computing (MCC) combines cloud computing and mobile devices to provide the benefits for mobile users, network operators and cloud providers also. Mobile devices have various problems like enter and leave the connection unpredictably, Limitation of battery power, frequent location changes, network signal loss, hardware failures and other common factors. Mobile devices appear and disappear in the network unpredictably. The proposed technique reduces the faults of mobile devices by using the past pattern of states and making the decision for predicting the future states of mobile devices. In this paper we have proposed a fault monitoring technique which is based on Hidden Markov Model (HMM) and Baum-Welch algorithm for analyzing and predicting the future resource state.
Keywords
cloud computing; fault tolerance; hidden Markov models; mobile computing; BAUM-WELCH algorithm; FTAB; HMM algorithm; MCC; battery power; cloud providers; fault monitoring; fault tolerance; hardware failures; hidden Markov model; mobile cloud computing; mobile devices; mobile users; network operators; network signal loss; Cloud computing; Fault tolerance; Fault tolerant systems; Hidden Markov models; Mobile communication; Mobile handsets; Monitoring; Hidden Markov model; cloud computing; mobile cloud computing; monitoring time interval; pattern;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless and Optical Communications Networks (WOCN), 2013 Tenth International Conference on
Conference_Location
Bhopal
ISSN
2151-7681
Print_ISBN
978-1-4673-5997-9
Type
conf
DOI
10.1109/WOCN.2013.6616256
Filename
6616256
Link To Document