Pruning Edge Research with Latency Shears

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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.

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APA

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 (pp. 182–189). Association for Computing Machinery, Inc. https://doi.org/10.1145/3422604.3425943

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