Energy-Efficient Fault-Tolerant Data Storage and Processing in Mobile Cloud
Abstract—Despite the advances in hardware for hand-held mobile devices, resource-intensive applications < Final Year Projects 2016 > 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 mobile cloud, 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.
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