Coded Wireless Distributed Computing With Packet Losses and Retransmissions

In wireless distributed computing systems, mobile devices that are connected wirelessly to the Fog (e.g., small base stations) collaboratively solve a given computational task. Unfortunately, wireless distributed computing systems suffer from packet losses due to severe channel fading. Moreover, a w...

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Bibliographic Details
Published in:IEEE transactions on wireless communications Vol. 20; no. 12; pp. 8204 - 8217
Main Authors: Han, Dong-Jun, Sohn, Jy-Yong, Moon, Jaekyun
Format: Journal Article
Language:English
Published: New York IEEE 01.12.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Coded computation
Codes
Computational modeling
Computer networks
Distributed computing
Distributed processing
Electronic devices
Fading channels
Guidelines
Mobile computing
Packet loss
straggler
Task analysis
Upper bounds
wireless distributed computing
Wireless networks
ISSN:1536-1276, 1558-2248
Online Access:Get full text
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Summary:In wireless distributed computing systems, mobile devices that are connected wirelessly to the Fog (e.g., small base stations) collaboratively solve a given computational task. Unfortunately, wireless distributed computing systems suffer from packet losses due to severe channel fading. Moreover, a wireless device can drop out of the system when leaving the coverage of a master node in the Fog layer. We model this unreliability between a device and a master node as a packet erasure channel. When a packet fails to be detected at the receiver, the corresponding packet is retransmitted, which would significantly increase the overall run-time to finish the task. We take a coding-theoretic approach to tackle this straggler-like problem in wireless distributed computing. We first investigate the expected latency using an <inline-formula> <tex-math notation="LaTeX">(n, k) </tex-math></inline-formula> maximum-distance separable (MDS) code. We obtain the lower and upper bounds on the latency in closed forms and provide guidelines to design MDS codes depending on the channel condition characterized by packet erasure probability. Then, we introduce another important performance metric called minimum latency , and also provide guidelines on designing optimal codes. Based on optimal codes, we obtain the performance curves of achievable minimum latency and achievable workload as functions of packet erasure probability.
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ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2021.3091465