Adaptive and Heterogeneity-Aware Coded Cooperative Computation at the Edge

Adaptive and Heterogeneity-Aware Coded Cooperative Computation at the Edge
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DOI:
10.1109/tmc.2021.3106250
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发表时间:
2021-08
影响因子:
7.9
通讯作者:
Yasaman Keshtkarjahromi;Yuxuan Xing;H. Seferoglu
Yasaman Keshtkarjahromi;Yuxuan Xing;H. Seferoglu
中科院分区:
计算机科学2区
文献类型:
--
作者:
Yasaman Keshtkarjahromi;Yuxuan Xing;H. Seferoglu

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协同计算是一种很有前途的边缘局部数据处理方法,例如物联网。协作计算主张将设备中的计算密集型任务划分为子任务,并将其分流到邻近的其他设备或服务器。然而,由于边缘设备的异构性和时变性,开发协作计算的潜力是具有挑战性的。编码计算提倡通过使用擦除码在子任务中混合数据,并将这些子任务卸载到其他设备进行计算,由于其更高的可靠性、更小的延迟和更低的通信成本,最近受到了越来越多的关注。本文针对边缘设备资源的异构性和时变性,提出了一种编码式协同计算框架--编码式协同计算协议(C3P)。C3P动态地将编码子任务卸载给帮助器,并自适应时变的资源。结果表明:(1)C3P的任务完成延迟非常接近最优编码协同计算方案;(2)C3P在资源利用率方面的效率高于99$99%;(3)C3P的任务完成延迟与基线相比有显著的改善,通过仿真和在真实的Android智能手机测试床上实现。
Cooperative computation is a promising approach for localized data processing at the edge, e.g., for Internet of Things (IoT). Cooperative computation advocates that computationally intensive tasks in a device could be divided into sub-tasks, and offloaded to other devices or servers in close proximity. However, exploiting the potential of cooperative computation is challenging mainly due to the heterogeneous and time-varying nature of edge devices. Coded computation, which advocates mixing data in sub-tasks by employing erasure codes and offloading these sub-tasks to other devices for computation, is recently gaining interest, thanks to its higher reliability, smaller delay, and lower communication costs. In this article, we develop a coded cooperative computation framework, which we name Coded Cooperative Computation Protocol (C3P), by taking into account the heterogeneous and time-varying resources of edge devices. C3P dynamically offloads coded sub-tasks to helpers and is adaptive to time-varying resources. We show that (i) task completion delay of C3P is very close to optimal coded cooperative computation solutions, (ii) the efficiency of C3P in terms of resource utilization is higher than $99\%$99%, and (iii) C3P improves task completion delay significantly as compared to baselines via both simulations and in a testbed consisting of real Android-based smartphones.