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Workload-aware Management Targeting Multi-Gateway Internet-of-Things

Authors:

Ioannis Galanis,

Theodoros Marinakis,

Iraklis AnagnostopoulosAuthors Info & Claims

COINS '19: Proceedings of the International Conference on Omni-Layer Intelligent Systems

Pages 110 - 115

https://doi.org/10.1145/3312614.3312639

Published: 05 May 2019 Publication History

Abstract

Edge Computing has risen as a new promising computing paradigm, that relies on connected devices to communicate and exchange data closer to the end-user. Specifically, gateways are a critical component as they receive requests from multiple edge devices and perform data processing. However, the continuously increased number of edge devices that each gateway serves and the growing network traffic result in (1) unbalanced workload execution of applications offloaded on the gateway; and (2) unequal distribution of workloads in multi-gateway environments. In this paper, we propose (1) an intra-gateway methodology to detect and balance application slowdown in terms of local unevenly distributed progress; and (2) a distributed inter-gateway methodology to balance workload among multiple gateways, in order to achieve a global progress threshold.

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Cited By

Galanis IPerala SKinley LAnagnostopoulos I(2021)Edge-First Resource Management for Video-Based Applications: A Face Detection Use CaseIEEE Embedded Systems Letters10.1109/LES.2020.299640213:2(33-36)Online publication date: Jun-2021
https://doi.org/10.1109/LES.2020.2996402
Dickerson JGalanis ITasoulas ZKinley LAnagnostopoulos I(2020)Adaptive Approximate Computing on Hardware Accelerators Targeting Internet-of-Things2020 IEEE 6th World Forum on Internet of Things (WF-IoT)10.1109/WF-IoT48130.2020.9221165(1-6)Online publication date: Jun-2020
https://doi.org/10.1109/WF-IoT48130.2020.9221165

Index Terms

Workload-aware Management Targeting Multi-Gateway Internet-of-Things

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cover image ACM Other conferences

COINS '19: Proceedings of the International Conference on Omni-Layer Intelligent Systems

May 2019

241 pages

ISBN:9781450366403

DOI:10.1145/3312614

Copyright © 2019 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]

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Publication History

Published: 05 May 2019

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COINS '19

COINS '19: INTERNATIONAL CONFERENCE ON OMNI-LAYER INTELLIGENT SYSTEMS

May 5 - 7, 2019

Crete, Greece

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Cited By

Galanis IPerala SKinley LAnagnostopoulos I(2021)Edge-First Resource Management for Video-Based Applications: A Face Detection Use CaseIEEE Embedded Systems Letters10.1109/LES.2020.299640213:2(33-36)Online publication date: Jun-2021
https://doi.org/10.1109/LES.2020.2996402
Dickerson JGalanis ITasoulas ZKinley LAnagnostopoulos I(2020)Adaptive Approximate Computing on Hardware Accelerators Targeting Internet-of-Things2020 IEEE 6th World Forum on Internet of Things (WF-IoT)10.1109/WF-IoT48130.2020.9221165(1-6)Online publication date: Jun-2020
https://doi.org/10.1109/WF-IoT48130.2020.9221165

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