Pruning Edge Research with Latency Shears

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Mohan , N , Corneo , L , Zavodovski , A , Bayhan , S , Wong , W & Kangasharju , J 2020 , Pruning Edge Research with Latency Shears . in HotNets 2020 : Proceedings of the 19th ACM Workshop on Hot Topics in Networks . ACM , New York, NY , pp. 182-189 , ACM Workshop on Hot Topics in Networks , United States , 04/11/2020 .

Title: Pruning Edge Research with Latency Shears
Author: Mohan, Nitinder; Corneo, Lorenzo; Zavodovski, Aleksandr; Bayhan, Suzan; Wong, Walter; Kangasharju, Jussi
Contributor organization: Department of Computer Science
Collaborative Networking research group / Jussi Kangasharju
Helsinki Institute for Information Technology
Publisher: ACM
Date: 2020-11-04
Language: eng
Number of pages: 8
Belongs to series: HotNets 2020
ISBN: 9781450381451
Abstract: Edge computing has gained attention from both academia and industry by pursuing two significant challenges: 1) moving latency critical services closer to the users, 2) saving network bandwidth by aggregating large flows before sending them to the cloud. While the rationale appeared sound at its inception almost a decade ago, several current trends are impacting it. Clouds have spread geographically reducing end-user latency, mobile phones? computing capabilities are improving, and network bandwidth at the core keeps increasing. In this paper, we scrutinize edge computing, examining its outlook and future in the context of these trends. We perform extensive client-to-cloud measurements using RIPE Atlas, and show that latency reduction as motivation for edge is not as persuasive as once believed; for most applications the cloud is already 'close enough' for majority of the world's population. This implies that edge computing may only be applicable for certain application niches, as opposed to a general-purpose solution.
Subject: cloud computing
cloud reachability
edge computing
internet measurements
113 Computer and information sciences
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion

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