Wireless Map-Reduce Distributed Computing with Full-Duplex Radios and Imperfect CSI

Sukjong Ha; Jingjing Zhang; Osvaldo Simeone; Joonhyuk Kang

doi:10.1109/SPAWC.2019.8815393

Wireless Map-Reduce Distributed Computing with Full-Duplex Radios and Imperfect CSI

Sukjong Ha, Jingjing Zhang, Osvaldo Simeone, Joonhyuk Kang

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

Consider a distributed computing system in which the worker nodes are connected over a shared wireless channel. Nodes can store a fraction of the data set over which computation needs to be carried out, and a Map-Shuffle-Reduce protocol is followed in order to enable collaborative processing. If there exists some level of redundancy among the computations performed at the nodes, the inter-node communication load during the Shuffle phase can be reduced by using either coded multicasting or cooperative transmission. It was previously shown that the latter approach is able to reduce the high-Signal-to-Noise Ratio communication load by half in the presence of full-duplex nodes and perfect transmit-side Channel State Information (CSI). In this paper, a novel scheme based on superposition coding is proposed that is demonstrated to outperform both coded multicasting and cooperative transmission under the assumption of imperfect CSI.

Original language	English (US)
Title of host publication	2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538665282
DOIs	https://doi.org/10.1109/SPAWC.2019.8815393
State	Published - Jul 2019
Event	20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019 - Cannes, France Duration: Jul 2 2019 → Jul 5 2019

Publication series

Name	IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume	2019-July

Conference

Conference	20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019
Country/Territory	France
City	Cannes
Period	7/2/19 → 7/5/19

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering
Computer Science Applications
Information Systems

Keywords

Imperfect CSI
Map-Reduce
Wireless distributed computing

Access to Document

10.1109/SPAWC.2019.8815393

Cite this

Ha, S., Zhang, J., Simeone, O., & Kang, J. (2019). Wireless Map-Reduce Distributed Computing with Full-Duplex Radios and Imperfect CSI. In 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019 Article 8815393 (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2019-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPAWC.2019.8815393

Ha, Sukjong ; Zhang, Jingjing ; Simeone, Osvaldo et al. / Wireless Map-Reduce Distributed Computing with Full-Duplex Radios and Imperfect CSI. 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC).

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abstract = "Consider a distributed computing system in which the worker nodes are connected over a shared wireless channel. Nodes can store a fraction of the data set over which computation needs to be carried out, and a Map-Shuffle-Reduce protocol is followed in order to enable collaborative processing. If there exists some level of redundancy among the computations performed at the nodes, the inter-node communication load during the Shuffle phase can be reduced by using either coded multicasting or cooperative transmission. It was previously shown that the latter approach is able to reduce the high-Signal-to-Noise Ratio communication load by half in the presence of full-duplex nodes and perfect transmit-side Channel State Information (CSI). In this paper, a novel scheme based on superposition coding is proposed that is demonstrated to outperform both coded multicasting and cooperative transmission under the assumption of imperfect CSI.",

keywords = "Imperfect CSI, Map-Reduce, Wireless distributed computing",

author = "Sukjong Ha and Jingjing Zhang and Osvaldo Simeone and Joonhyuk Kang",

note = "Funding Information: The work of S. Ha and J. Kang was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2017R1A2B2012698). J. Zhang and O. Simeone have received funding from the European Research Council (ERC) under the European Unions Horizon 2020 Research and Innovation Programme (Grant Agreement No. 725731). The work of O. Simeone was also funded in part by the U.S. National Science Foundation under Grant 1525629. Publisher Copyright: {\textcopyright} 2019 IEEE.; 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019 ; Conference date: 02-07-2019 Through 05-07-2019",

year = "2019",

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doi = "10.1109/SPAWC.2019.8815393",

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Ha, S, Zhang, J, Simeone, O & Kang, J 2019, Wireless Map-Reduce Distributed Computing with Full-Duplex Radios and Imperfect CSI. in 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019., 8815393, IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, vol. 2019-July, Institute of Electrical and Electronics Engineers Inc., 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019, Cannes, France, 7/2/19. https://doi.org/10.1109/SPAWC.2019.8815393

Wireless Map-Reduce Distributed Computing with Full-Duplex Radios and Imperfect CSI. / Ha, Sukjong; Zhang, Jingjing; Simeone, Osvaldo et al.
2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8815393 (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2019-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: The work of S. Ha and J. Kang was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2017R1A2B2012698). J. Zhang and O. Simeone have received funding from the European Research Council (ERC) under the European Unions Horizon 2020 Research and Innovation Programme (Grant Agreement No. 725731). The work of O. Simeone was also funded in part by the U.S. National Science Foundation under Grant 1525629. Publisher Copyright: © 2019 IEEE.

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N2 - Consider a distributed computing system in which the worker nodes are connected over a shared wireless channel. Nodes can store a fraction of the data set over which computation needs to be carried out, and a Map-Shuffle-Reduce protocol is followed in order to enable collaborative processing. If there exists some level of redundancy among the computations performed at the nodes, the inter-node communication load during the Shuffle phase can be reduced by using either coded multicasting or cooperative transmission. It was previously shown that the latter approach is able to reduce the high-Signal-to-Noise Ratio communication load by half in the presence of full-duplex nodes and perfect transmit-side Channel State Information (CSI). In this paper, a novel scheme based on superposition coding is proposed that is demonstrated to outperform both coded multicasting and cooperative transmission under the assumption of imperfect CSI.

AB - Consider a distributed computing system in which the worker nodes are connected over a shared wireless channel. Nodes can store a fraction of the data set over which computation needs to be carried out, and a Map-Shuffle-Reduce protocol is followed in order to enable collaborative processing. If there exists some level of redundancy among the computations performed at the nodes, the inter-node communication load during the Shuffle phase can be reduced by using either coded multicasting or cooperative transmission. It was previously shown that the latter approach is able to reduce the high-Signal-to-Noise Ratio communication load by half in the presence of full-duplex nodes and perfect transmit-side Channel State Information (CSI). In this paper, a novel scheme based on superposition coding is proposed that is demonstrated to outperform both coded multicasting and cooperative transmission under the assumption of imperfect CSI.

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Ha S, Zhang J, Simeone O, Kang J. Wireless Map-Reduce Distributed Computing with Full-Duplex Radios and Imperfect CSI. In 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8815393. (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC). doi: 10.1109/SPAWC.2019.8815393

Wireless Map-Reduce Distributed Computing with Full-Duplex Radios and Imperfect CSI

Abstract

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All Science Journal Classification (ASJC) codes

Keywords

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