Optimal Offloading for Dynamic Compute-Intensive Applications in Wireless Networks

Bin Li
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Abstract

With the rapid growth of wireless compute-intensive services (such as image recognition, real-time language translation, or other artificial intelligence applications), efficient wireless algorithm design should not only address when and which users should transmit at each time instance (referred to as wireless scheduling) but also determine where the computation should be executed (referred to as offloading decision) with the goal of minimizing both computing latency and energy consumption. Despite the presence of a variety of earlier works on the efficient offloading design in wireless networks, to the best of our knowledge, there does not exist a work on the realistic user- level dynamic model, where each incoming user demands a heavy computation and leaves the system once its computing request is completed. To this end, we formulate a problem of an optimal offloading design in the presence of dynamic compute-intensive applications in wireless networks. Then, we show that there exists a fundamental logarithmic energy- workload tradeoff for any feasible offloading algorithm, and develop an optimal threshold-based offloading algorithm that achieves this fundamental logarithmic bound.
无线网络中动态计算密集型应用的最佳卸载
随着无线计算密集型服务(如图像识别、实时语言翻译或其他人工智能应用)的快速增长,高效的无线算法设计不仅应该解决用户在每个时间实例中应该何时以及哪些传输(称为无线调度),还应该确定应该在哪里执行计算(称为卸载决策),目标是最小化计算延迟和能耗。尽管在无线网络中存在各种各样的高效卸载设计的早期工作,但据我们所知,还没有一个现实的用户级动态模型的工作,其中每个进入的用户需要大量的计算,并在其计算请求完成后离开系统。为此,我们提出了无线网络中动态计算密集型应用的最优卸载设计问题。然后,我们证明了任何可行的卸载算法都存在基本对数能量-工作负载权衡,并开发了一个基于阈值的最优卸载算法来实现这个基本对数界限。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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