Energy-Efficient Fault-Tolerant Data Storage and Processing in Mobile Cloud
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Authors
Chen, Chien-An
Won, Myounggyu
Stoleru, Radu
Xie, Geoffrey G.
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Date of Issue
2015
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Abstract
Despite the advances in hardware for hand-held mobile devices, resource-intensive applications (e.g., video and image storage and processing or map-reduce type) still remain off bounds since they require large computation and storage capabilities. Recent research has attempted to address these issues by employing remote servers, such as clouds and peer mobile devices. For mobile devices deployed in dynamic networks (i.e., with frequent topology changes because of node failure/unavailability and mobility as in a mobile cloud), however, challenges of reliability and energy efficiency remain largely unaddressed. To the best of our knowledge, we are the first to address these challenges in an integrated manner for both data storage and processing in mobilecloud, an approach we call k-out-of-n computing. In our solution, mobile devices successfully retrieve or process data, in the most energy-efficient way, as long as k out of n remote servers are accessible. Through a real system implementation we prove the feasibility of our approach. Extensive simulations demonstrate the fault tolerance and energy efficiency performance of our framework in larger scale networks.
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Article
Description
IEEE Transactions on Cloud Computing
The article of record as published may be found at http://dx.doi.org/10.1
The article of record as published may be found at http://dx.doi.org/10.1
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Computer Science (CS)
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Funded by Naval Postgraduate School
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Naval Postgraduate School (N00244-12-1-0035)
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.