Dynamic Heterogeneity-Aware Coded Cooperative Computation at the Edge

Dynamic Heterogeneity-Aware Coded Cooperative Computation at the Edge
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DOI:
10.1109/icnp.2018.00013
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发表时间:
2018-01
期刊:
2018 IEEE 26th International Conference on Network Protocols (ICNP)
影响因子:
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通讯作者:
Yasaman Keshtkarjahromi;Yuxuan Xing;H. Seferoglu
Yasaman Keshtkarjahromi;Yuxuan Xing;H. Seferoglu
中科院分区:
其他
文献类型:
--
作者:
Yasaman Keshtkarjahromi;Yuxuan Xing;H. Seferoglu

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协作计算是用于边缘处的局部化数据处理的有前途的方法,例如,物联网(IoT)。协同计算主张将设备中的计算密集型任务划分为子任务,并将其卸载到邻近的其他设备或服务器上。然而,利用协作计算的潜力是具有挑战性的,主要是由于边缘设备的异构性和时变性。编码计算提倡通过使用纠删码将数据混合在子任务中,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,最近引起了人们的兴趣。在本文中,我们开发了一个编码的协同计算框架,我们命名为编码的协同计算协议(C3P),考虑到边缘设备的异构资源。C3P动态地将编码的子任务卸载到助手,并且适应时变资源。我们表明,(i)C3P的任务完成延迟是非常接近的最佳编码的协同计算解决方案,(ii)C3P的效率在资源利用率高于99%,(iii)C3P改善任务完成延迟显着基线相比,通过模拟和测试床组成的真实的基于Android的智能手机。
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 paper, we develop a coded cooperative computation framework, which we name Coded Cooperative Computation Protocol (C3P), by taking into account the heterogeneous 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%, (iii) C3P improves task completion delay significantly as compared to baselines via both simulations and in a test-bed consisting of real Android-based smartphones.