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Coded Federated Computing in Wireless Networks with Straggling Devices and Imperfect CSI

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arxiv 1901.05239 v1 pith:LHGZKUIP submitted 2019-01-16 cs.IT math.IT

classification cs.ITmath.IT
keywords computingwirelesscodeddistributedprocessorsdatafederatedimperfect
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Distributed computing platforms typically assume the availability of reliable and dedicated connections among the processors. This work considers an alternative scenario, relevant for wireless data centers and federated learning, in which the distributed processors, operating on generally distinct coded data, are connected via shared wireless channels accessed via full-duplex transmission. The study accounts for both wireless and computing impairments, including interference, imperfect Channel State Information, and straggling processors, and it assumes a Map-Shuffle-Reduce coded computing paradigm. The total latency of the system, obtained as the sum of computing and communication delays, is studied for different shuffling strategies revealing the interplay between distributed computing, coding, and cooperative or coordinated transmission.

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Cited by 1 Pith paper

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  1. Scheduling Policies for Federated Learning in Wireless Networks

    cs.IT 2019-08 conditional novelty 6.0 of 10

    The convergence rate of wireless federated learning is governed by a scheduling-and-decoding success probability, with proportional fair best at high SINR and round robin best at low SINR.

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