The hidden cost of the edge: A performance comparison of edge and cloud latencies
Paper i proceeding, 2021

Edge computing has emerged as a popular paradigm for running latency-sensitive applications due to its ability to offer lower network latencies to end-users. In this paper, we argue that despite its lower network latency, the resource-constrained nature of the edge can result in higher end-To-end latency, especially at higher utilizations, when compared to cloud data centers. We study this edge performance inversion problem through an analytic comparison of edge and cloud latencies and analyze conditions under which the edge can yield worse performance than the cloud. To verify our analytic results, we conduct a detailed experimental comparison of the edge and the cloud latencies using a realistic application and real cloud workloads. Both our analytical and experimental results show that even at moderate utilizations, the edge queuing delays can offset the benefits of lower network latencies, and even result in performance inversion where running in the cloud would provide superior latencies. We finally discuss practical implications of our results and provide insights into how application designers and service providers should design edge applications and systems to avoid these pitfalls.


Ahmed Ali-Eldin Hassan

Nätverk och System

Bin Wang

University of Massachusetts

Prashant Shenoy

University of Massachusetts

International Conference for High Performance Computing, Networking, Storage and Analysis, SC

21674329 (ISSN) 21674337 (eISSN)

9781450384421 (ISBN)

33rd International Conference for High Performance Computing, Networking, Storage and Analysis: Science and Beyond, SC 2021
Virtual, Online, USA,






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