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. This abstract presents a mathematical model for both optimizing energy consumption and meeting the fault tolerance requirements of data storage and processing under a dynamic network topology. Our method presents an efficient algorithm for estimating the communication cost in a mobile cloud, where nodes fail or move, joining/leaving the network. This abstract presents the first process scheduling algorithm that is both fault-tolerant and energy efficient. It presents a distributed protocol for continually monitoring the network topology, without requiring additional packet transmissions. It presents the evaluation of our proposed frame-work through a real hardware implementation and large scale simulations.
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