University of Oulu

Lovén, L., Peltonen, E., Ruha, L. et al. A dark and stormy night: Reallocation storms in edge computing. J Wireless Com Network 2022, 86 (2022). https://doi.org/10.1186/s13638-022-02170-y

A dark and stormy night : reallocation storms in edge computing

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Author: Lovén, Lauri1; Peltonen, Ella1; Ruha, Leena2;
Organizations: 1Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
2Natural Resources Institute Finland, Oulu, Finland
3Center for Wireless Communication, University of Oulu, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022092159725
Language: English
Published: Springer Nature, 2022
Publish Date: 2022-09-21
Description:

Abstract

Efficient resource usage in edge computing requires clever allocation of the workload of application components. In this paper, we show that under certain circumstances, the number of superfluous workload reallocations from one edge server to another may grow to a significant proportion of all user tasks—a phenomenon we present as a reallocation storm. We showcase this phenomenon on a city-scale edge server deployment by simulating the allocation of user task workloads in a number of scenarios capturing likely edge computing deployments and usage patterns. The simulations are based on a large real-world data set of city-wide Wi-Fi network connections, with more than 47M connections over ca. 560 access points. We study the occurrence of reallocation storms in three common edge-based reallocation strategies and compare the latency–workload trade-offs related to each strategy. As a result, we find that the superfluous reallocations vanish when the edge server capacity is increased above a certain threshold, unique for each reallocation strategy, peaking at ca. 35% of the peak ES workload. Further, while a reallocation strategy aiming to minimize latency consistently resulted in the worst reallocation storms, the two other strategies, namely a random reallocation strategy and a bottom-up strategy which always chooses the edge server with the lowest workload as a reallocation target, behave nearly identically in terms of latency as well as the reallocation storm in dense edge deployments. Since the random strategy requires much less coordination, we recommend it over the bottom-up one in dense ES deployments. Moreover, we study the conditions associated with reallocation storms. We discover that edge servers with the very highest workloads are best associated with reallocation storms, with other servers around the few busy nodes thus mirroring their workload. Further, we identify circumstances associated with an elevated risk of reallocation storms, such as summertime (ca. 4 times the risk than on average) and on weekends (ca. 1.5 times the risk). Furthermore, mass events such as popular sports games incurred a high risk (nearly 10 times that of the average) of a reallocation storm in a MEC-based scenario.

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Series: EURASIP journal on wireless communications and networking
ISSN: 1687-1472
ISSN-E: 1687-1499
ISSN-L: 1687-1472
Volume: 2022
Article number: 86
DOI: 10.1186/s13638-022-02170-y
OADOI: https://oadoi.org/10.1186/s13638-022-02170-y
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
1171 Geosciences
Subjects:
Funding: This research is supported by Academy of Finland 6Genesis Flagship and DigiHealth programs (grants 318927, 326291); the ECSEL JU FRACTAL (grant 877056), receiving support from the EU Horizon 2020 programme and Spain, Italy, Austria, Germany, France, Finland, Switzerland; and the Infotech Oulu research institute.
EU Grant Number: (877056) FRACTAL - A Cognitive Fractal and Secure EDGE based on an unique Open-Safe-Reliable-Low Power Hardware Platform Node
Academy of Finland Grant Number: 318927
326291
Detailed Information: 318927 (Academy of Finland Funding decision)
326291 (Academy of Finland Funding decision)
Copyright information: © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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