research-article

Edge computing in the ePC: a reality check

Authors:

Ilija Hadžić,

Hans C. WoitheAuthors Info & Claims

SEC '17: Proceedings of the Second ACM/IEEE Symposium on Edge Computing

Article No.: 13, Pages 1 - 10

https://doi.org/10.1145/3132211.3134449

Published: 12 October 2017 Publication History

Abstract

Mobile Edge Computing (MEC) has received much attention from the research community in recent years. A significant part of the published work has studied the telecom-centric MEC architecture, which assumes that the computing resource is located at the edge of the mobile access network (e.g., the Evolved Packet Core), typically at the first aggregation level. Many authors make a silent assumption in their analyses that the latency at this stage of the network is negligible. In this paper we show not only that this assumption false, but that in some common cases the latency of the first-aggregation stage dominates the end-to-end latency. We challenge the latency argument in the context of present-day access networks and discuss what must be done to pave the way for practical deployments of MEC.

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Cited By

Zhang WFeng MKrunz M(2024)Latency Estimation and Computational Task Offloading in Vehicular Mobile Edge Computing ApplicationsIEEE Transactions on Vehicular Technology10.1109/TVT.2023.333419273:4(5808-5823)Online publication date: Apr-2024
https://doi.org/10.1109/TVT.2023.3334192
Ortegat GGrolaux DRiviere EVanderdonckt J(2022)Engineering the Transition of Interactive Collaborative Software from Cloud Computing to Edge ComputingProceedings of the ACM on Human-Computer Interaction10.1145/35322106:EICS(1-31)Online publication date: 17-Jun-2022
https://dl.acm.org/doi/10.1145/3532210
Rahmanian AAli-Eldin ASkubic BElmroth E(2022)MicroSplit: Efficient Splitting of Microservices on Edge Clouds2022 IEEE/ACM 7th Symposium on Edge Computing (SEC)10.1109/SEC54971.2022.00027(252-264)Online publication date: Dec-2022
https://doi.org/10.1109/SEC54971.2022.00027
Show More Cited By

Index Terms

Edge computing in the ePC: a reality check
1. Networks
  1. Network components
    1. Wireless access points, base stations and infrastructure
  2. Network performance evaluation
    1. Network measurement

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Information & Contributors

Information

Published In

cover image ACM Conferences

SEC '17: Proceedings of the Second ACM/IEEE Symposium on Edge Computing

October 2017

365 pages

ISBN:9781450350877

DOI:10.1145/3132211

General Chair:
Junshan Zhang
Arizona State University
,
Program Chairs:
Mung Chiang
Purdue University and Princeton Edge Lab
,
Bruce Maggs
Akamai/Duke University

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
IEEE-CS\DATC: IEEE Computer Society

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 October 2017

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Research-article

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SEC '17

Sponsor:

SIGMOBILE
IEEE-CS\DATC

SEC '17: IEEE/ACM Symposium on Edge Computing

October 12 - 14, 2017

California, San Jose

Acceptance Rates

SEC '17 Paper Acceptance Rate 20 of 41 submissions, 49%;

Overall Acceptance Rate 40 of 100 submissions, 40%

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Cited By

Zhang WFeng MKrunz M(2024)Latency Estimation and Computational Task Offloading in Vehicular Mobile Edge Computing ApplicationsIEEE Transactions on Vehicular Technology10.1109/TVT.2023.333419273:4(5808-5823)Online publication date: Apr-2024
https://doi.org/10.1109/TVT.2023.3334192
Ortegat GGrolaux DRiviere EVanderdonckt J(2022)Engineering the Transition of Interactive Collaborative Software from Cloud Computing to Edge ComputingProceedings of the ACM on Human-Computer Interaction10.1145/35322106:EICS(1-31)Online publication date: 17-Jun-2022
https://dl.acm.org/doi/10.1145/3532210
Rahmanian AAli-Eldin ASkubic BElmroth E(2022)MicroSplit: Efficient Splitting of Microservices on Edge Clouds2022 IEEE/ACM 7th Symposium on Edge Computing (SEC)10.1109/SEC54971.2022.00027(252-264)Online publication date: Dec-2022
https://doi.org/10.1109/SEC54971.2022.00027
Gourav KKaur A(2022)Computation Offloading Scheme Classification Using Cloud-Edge Computing for Internet of Vehicles (IoV)International Conference on Innovative Computing and Communications10.1007/978-981-19-2821-5_39(459-485)Online publication date: 27-Sep-2022
https://doi.org/10.1007/978-981-19-2821-5_39
Yang YChen XTan RXiao Y(2021)Dynamic Service Provisioning FrameworksIntelligent IoT for the Digital World10.1002/9781119593584.ch4(149-196)Online publication date: 16-Apr-2021
https://doi.org/10.1002/9781119593584.ch4
Mohan NCorneo LZavodovski ABayhan SWong WKangasharju JZhao BZheng HMadhyastha HPadmanabhan V(2020)Pruning Edge Research with Latency ShearsProceedings of the 19th ACM Workshop on Hot Topics in Networks10.1145/3422604.3425943(182-189)Online publication date: 4-Nov-2020
https://dl.acm.org/doi/10.1145/3422604.3425943
Xia RXiao YLi YKrunz MNiyato D(2020)A Generative Learning Approach for Spatio-temporal Modeling in Connected Vehicular NetworkICC 2020 - 2020 IEEE International Conference on Communications (ICC)10.1109/ICC40277.2020.9149319(1-6)Online publication date: Jun-2020
https://doi.org/10.1109/ICC40277.2020.9149319
Nguyen CMehta AKlein CElmroth EChen SOnishi RAnanthanarayanan GLi Q(2019)Why cloud applications are not ready for the edge (yet)Proceedings of the 4th ACM/IEEE Symposium on Edge Computing10.1145/3318216.3363298(250-263)Online publication date: 7-Nov-2019
https://dl.acm.org/doi/10.1145/3318216.3363298
Xiao YKrunz MVolos HBando T(2019)Driving in the Fog: Latency Measurement, Modeling, and Optimization of LTE-based Fog Computing for Smart Vehicles2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)10.1109/SAHCN.2019.8824922(1-9)Online publication date: Jun-2019
https://doi.org/10.1109/SAHCN.2019.8824922
Al-Qamash ASoliman IAbulibdeh RSaleh M(2018)Cloud, Fog, and Edge Computing: A Software Engineering Perspective2018 International Conference on Computer and Applications (ICCA)10.1109/COMAPP.2018.8460443(276-284)Online publication date: Aug-2018
https://doi.org/10.1109/COMAPP.2018.8460443

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