[논문]Coded Wireless Distributed Computing With Packet Losses and Retransmissions

Han, Dong-Jun; Sohn, Jy-Yong; Moon, Jaekyun

doi:10.1109/twc.2021.3091465

[해외논문] Coded Wireless Distributed Computing With Packet Losses and Retransmissions 원문보기

IEEE transactions on wireless communications, v.20 no.12, 2021년, pp.8204 - 8217

Han, Dong-Jun (Korea Advanced Institute of Science and Technology (KAIST), School of Electrical Engineering, Daejeon, South Korea) , Sohn, Jy-Yong (University of Wisconsin–) , Moon, Jaekyun (Madison, Madison, WI, USA)

Abstract ▼ AI-Helper

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 $(n, k)$ 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.

참고문헌 (42)

Markov Chains Gibbs Fields Monte Carlo Simulation and Queues bremaud 1999 10.1007/978-1-4757-3124-8
10.1109/ISIT.2017.8006962
10.1109/GLOCOMW.2016.7848828
10.1109/GLOCOM.2016.7841903
Li, Songze, Maddah-Ali, Mohammad Ali, Yu, Qian, Avestimehr, A. Salman. A Fundamental Tradeoff Between Computation and Communication in Distributed Computing. IEEE transactions on information theory, vol.64, no.1, 109-128.

상세보기
10.1109/ALLERTON.2015.7447112
10.1109/ALLERTON.2017.8262881
Gerami, Majid, Ming Xiao, Jun Li, Fischione, Carlo, Zihuai Lin. Repair for Distributed Storage Systems With Packet Erasure Channels and Dedicated Nodes for Repair. IEEE transactions on communications, vol.64, no.4, 1367-1383.

상세보기
10.1109/GLOCOM.2016.7841903
Li, Songze, Yu, Qian, Maddah-Ali, Mohammad Ali, Avestimehr, A. Salman. A Scalable Framework for Wireless Distributed Computing. IEEE/ACM transactions on networking : a joint publication of the IEEE Communications Society, the IEEE Computer Society, and the ACM with its Special Interest Group on Data Communication, vol.25, no.5, 2643-2654.

상세보기
Zhu, Guangxu, Wang, Yong, Huang, Kaibin. Broadband Analog Aggregation for Low-Latency Federated Edge Learning. IEEE transactions on wireless communications, vol.19, no.1, 491-506.

상세보기
10.1109/WCNC.2005.1424754
Lee, Kangwook, Lam, Maximilian, Pedarsani, Ramtin, Papailiopoulos, Dimitris, Ramchandran, Kannan. Speeding Up Distributed Machine Learning Using Codes. IEEE transactions on information theory, vol.64, no.3, 1514-1529.

상세보기
10.1109/ISIT.2017.8006963
Proc Neural Inf Process Syst Polynomial codes: An optimal design for high-dimensional coded matrix multiplication yu 2017 4406
Proc Neural Inf Process Syst ‘Short-Dot’: Computing large linear transforms distributedly using coded short dot products dutta 2016 2092
Proc Int Conf Mach Learn Gradient coding: Avoiding stragglers in distributed learning tandon 2017 3368
Proc ICML DRACO: Byzantine-resilient distributed training via redundant gradients chen 2018 903
Proc Int Conf Mach Learn Communication-computation efficient gradient coding ye 2018 5610
arXiv 1902 01981 CodedReduce: A fast and robust framework for gradient aggregation in distributed learning reisizadeh 2019
Proc 22nd Int Conf Artif Intell Statist Lagrange coded computing: Optimal design for resiliency, security, and privacy yu 2019 1215
10.1109/ISIT.2019.8849317
He, Yinghui, Ren, Jinke, Yu, Guanding, Cai, Yunlong. D2D Communications Meet Mobile Edge Computing for Enhanced Computation Capacity in Cellular Networks. IEEE transactions on wireless communications, vol.18, no.3, 1750-1763.

상세보기
Reisizadeh, Amirhossein, Prakash, Saurav, Pedarsani, Ramtin, Avestimehr, Amir Salman. Coded Computation Over Heterogeneous Clusters. IEEE transactions on information theory, vol.65, no.7, 4227-4242.

상세보기
Li, Fan, Chen, Jinyuan, Wang, Zhiying. Wireless MapReduce Distributed Computing. IEEE transactions on information theory, vol.65, no.10, 6101-6114.

상세보기
Wang, Feng, Xu, Jie, Wang, Xin, Cui, Shuguang. Joint Offloading and Computing Optimization in Wireless Powered Mobile-Edge Computing Systems. IEEE transactions on wireless communications, vol.17, no.3, 1784-1797.

상세보기
10.1109/ISIT.2018.8437669
You, Changsheng, Huang, Kaibin, Chae, Hyukjin, Kim, Byoung-Hoon. Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading. IEEE transactions on wireless communications, vol.16, no.3, 1397-1411.

상세보기
Yang, Kai, Jiang, Tao, Shi, Yuanming, Ding, Zhi. Federated Learning via Over-the-Air Computation. IEEE transactions on wireless communications, vol.19, no.3, 2022-2035.

상세보기
Ren, Jinke, Yu, Guanding, Cai, Yunlong, He, Yinghui. Latency Optimization for Resource Allocation in Mobile-Edge Computation Offloading. IEEE transactions on wireless communications, vol.17, no.8, 5506-5519.

상세보기
Datla, Dinesh, Kim, Jeong-Ho, Chen, Xuetao, Tsou, Thomas, Raghunandan, Sahana, Hasan, S.M. Shajedul, Reed, Jeffrey H., Dietrich, Carl B., Bose, Tamal, Fette, Bruce. Wireless distributed computing: a survey of research challenges. IEEE communications magazine, vol.50, no.1, 144-152.

상세보기
Amiri, Mohammad Mohammadi, Gündüz, Deniz. Federated Learning Over Wireless Fading Channels. IEEE transactions on wireless communications, vol.19, no.5, 3546-3557.

상세보기
10.1109/ISIT.2019.8849747
Proc Neural Inf Process Syst Election coding for distributed learning: Protecting SignSGD against byzantine attacks sohn 2020
10.1109/ALLERTON.2017.8262778
10.1109/ISIT.2017.8006960
10.1109/ISIT.2017.8007060
10.1145/3393691.3394214
10.2307/1266548
10.1109/ISIT.2019.8849306
10.1109/ISIT.2018.8437871
10.1109/ISIT.2018.8437473

LOADING...

활용도 분석정보

상세보기

다운로드

내보내기

활용도 Top5 논문

해당 논문의 주제분야에서 활용도가 높은 상위 5개 콘텐츠를 보여줍니다.
더보기 버튼을 클릭하시면 더 많은 관련자료를 살펴볼 수 있습니다.

원문 보기

AccessON 원문보기

원문 URL 링크

DOI : 10.1109/TWC.2021.3091465
IEEE : 저널 > 논문
AccessON : 저널

*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.

오픈액세스(OA) 유형

BRONZE

출판사/학술단체 등이 한시적으로 특별한 프로모션 또는 일정기간 경과 후 접근을 허용하여, 출판사/학술단체 등의 사이트에서 이용 가능한 논문

저작권 관리 안내

내보내기 메뉴

내보내기 구분

파일저장
인쇄
메일전송

구성항목

기본정보
상세정보

관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관

저장형식

Text(ASCII format)
Excel format
RefWorks Direct Export
RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley

메일정보

받는사람 (필수): @
보내는사람 (선택): @
제목
내용: KISTI 검색결과 이메일 서비스

안내

총 건의 자료가 검색되었습니다.

다운받으실 자료의 인덱스를 입력하세요. (1-10,000)

검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다.

데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요)

다운로드 파일은 UTF-8 형태로 저장됩니다.
파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오.

Text(ASCII format)
Excel format

표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

AI-Helper ※ AI-Helper는 을 사용합니다.

AI-Helper

안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

연합인증