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A dynamic execution offloading model for efficient mobile cloud computing

机译:用于高效移动云计算的动态执行卸载模型

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With the emerging of diverse applications, power-sensitive mobile devices are facing the severe challenge of computational stress. Many researchers propose the schemes of migrating the mobile devices' computational burden to their adjacent powerful cloud servers. In these schemes, the execution context as well as the program itself must be sent to the cloud. The transfer time is the key element affecting the performance. In this paper, we propose the scheme of shrinking and reusing the migrated data to accelerate the transmission process. Besides, on the cloud side, we design a caching algorithm of IB-LRU (Importance-based LRU) to manage the migrated data. We evaluate our scheme by comprehensive experiments. Our IB-LRU algorithm surpasses traditional caching algorithms such as LRU by discriminating frequently and infrequently referenced cached data. The experiment results show that our scheme significantly improves the overall performance of mobile application migration by reducing the transmission time.
机译:随着各种应用程序的出现,对功耗敏感的移动设备面临着计算压力的严峻挑战。许多研究人员提出了将移动设备的计算负担迁移到其相邻功能强大的云服务器的方案。在这些方案中,必须将执行上下文以及程序本身发送到云。传输时间是影响性能的关键因素。在本文中,我们提出了缩小和重用已迁移数据以加快传输过程的方案。此外,在云方面,我们设计了IB-LRU(基于重要性的LRU)的缓存算法来管理迁移的数据。我们通过综合实验评估我们的计划。我们的IB-LRU算法通过区分频繁引用和不频繁引用的缓存数据,超越了传统的缓存算法(例如LRU)。实验结果表明,该方案通过减少传输时间,显着提高了移动应用迁移的整体性能。

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