Energy-Efficient Fault-Tolerant Data Storage and Processing in Mobile Cloud
Energy-Efficient Fault-Tolerant Data Storage and Processing in Mobile Cloud
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DOI：
10.1109/tcc.2014.2326169
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发表时间：
2015
影响因子：
6.5
通讯作者：
Chien-An Chen;M. Won;R. Stoleru;G. Xie
中科院分区：
文献类型：
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作者：
Chien-An Chen;M. Won;R. Stoleru;G. Xie
尽管手持移动设备的硬件取得了进步，但资源密集型应用程序（例如视频和图像存储和处理或地图减少类型）仍然是禁区，因为它们需要大量的计算和存储能力。最近的研究试图通过使用远程服务器（如云和对等移动设备）来解决这些问题。然而，对于部署在动态网络中的移动设备（即，由于节点故障/不可用和移动云中的移动性而频繁更改拓扑），可靠性和能源效率的挑战在很大程度上仍未得到解决。据我们所知，我们是第一个以集成的方式解决这些挑战的移动云数据存储和处理，我们称之为k-out- n计算的方法。在我们的解决方案中，只要n个远程服务器中有k个可以访问，移动设备就可以以最节能的方式成功检索或处理数据。通过一个实际的系统实现，证明了该方法的可行性。大量的仿真证明了我们的框架在更大规模网络中的容错性和能效性能。
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 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. 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.