short-paper

Decentralized self-adaptive computing at the edge

Author:

Mirko D'AngeloAuthors Info & Claims

SEAMS '18: Proceedings of the 13th International Conference on Software Engineering for Adaptive and Self-Managing Systems

Pages 144 - 148

https://doi.org/10.1145/3194133.3194160

Published: 28 May 2018 Publication History

Abstract

Nowadays, computing infrastructures are usually deployed in fully controlled environments and managed in a centralized fashion. Leveraging on centralized infrastructures prevent the system to deal with scalability and performance issues, which are inherent to modern large-scale data-intensive applications. On the other hand, we envision fully decentralized computing infrastructures deployed at the edge of the network providing the required support for operating data-intensive systems. However, engineering such systems raises many challenges, as decentralization introduces uncertainty, which in turn may harm the dependability of the system. To this end, self-adaptation is a key approach to manage uncertainties at runtime and satisfy the requirements of decentralized data-intensive systems. This paper shows the research directions and current contributions towards this vision by (i) evaluating the impact of the distribution of computational entities, (ii) engineering decentralized computing through self-adaptation and, (iii) evaluating decentralized and self-adaptive applications.

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Cited By

Pervaiz AYang YDuracz ABartha FSai RImes CCartwright RPalem KLu SHoffmann HScholliers CSinger J(2022)GOAL: Supporting General and Dynamic Adaptation in Computing SystemsProceedings of the 2022 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software10.1145/3563835.3567655(16-32)Online publication date: 29-Nov-2022
https://dl.acm.org/doi/10.1145/3563835.3567655
Ghaferi EMalekhosseini RRad FBagherifard K(2022)A clustering method for locating services based on fog computing for the internet of thingsThe Journal of Supercomputing10.1007/s11227-022-04393-878:11(13756-13779)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1007/s11227-022-04393-8
Betancourt VLiu BBecker J(2021)Towards Policy-based Task Self-Reallocation in Dynamic Edge Computing Systems2021 IEEE 19th International Conference on Industrial Informatics (INDIN)10.1109/INDIN45523.2021.9557374(1-6)Online publication date: 21-Jul-2021
https://doi.org/10.1109/INDIN45523.2021.9557374
Show More Cited By

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Information & Contributors

Information

Published In

cover image ACM Conferences

SEAMS '18: Proceedings of the 13th International Conference on Software Engineering for Adaptive and Self-Managing Systems

May 2018

244 pages

ISBN:9781450357159

DOI:10.1145/3194133

General Chair:
Jesper Andersson
Linnaeus University, Sweden
,
Program Chair:
Danny Weyns
Katholieke Universiteit Leuven, Belgium | Linnaeus University, Sweden

Copyright © 2018 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGSOFT: ACM Special Interest Group on Software Engineering
IEEE-CS: Computer Society

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 May 2018

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ICSE '18

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SIGSOFT
IEEE-CS

ICSE '18: 40th International Conference on Software Engineering

May 28 - 29, 2018

Gothenburg, Sweden

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Overall Acceptance Rate 17 of 31 submissions, 55%

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Cited By

Pervaiz AYang YDuracz ABartha FSai RImes CCartwright RPalem KLu SHoffmann HScholliers CSinger J(2022)GOAL: Supporting General and Dynamic Adaptation in Computing SystemsProceedings of the 2022 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software10.1145/3563835.3567655(16-32)Online publication date: 29-Nov-2022
https://dl.acm.org/doi/10.1145/3563835.3567655
Ghaferi EMalekhosseini RRad FBagherifard K(2022)A clustering method for locating services based on fog computing for the internet of thingsThe Journal of Supercomputing10.1007/s11227-022-04393-878:11(13756-13779)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1007/s11227-022-04393-8
Betancourt VLiu BBecker J(2021)Towards Policy-based Task Self-Reallocation in Dynamic Edge Computing Systems2021 IEEE 19th International Conference on Industrial Informatics (INDIN)10.1109/INDIN45523.2021.9557374(1-6)Online publication date: 21-Jul-2021
https://doi.org/10.1109/INDIN45523.2021.9557374
Nezami ZZamanifar KDjemame KPournaras E(2021)Decentralized Edge-to-Cloud Load Balancing: Service Placement for the Internet of ThingsIEEE Access10.1109/ACCESS.2021.30749629(64983-65000)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3074962
Zhou FChen H(2021)DECS: Collaborative Edge-Edge Data Storage Service for Edge ComputingCollaborative Computing: Networking, Applications and Worksharing10.1007/978-3-030-67537-0_23(373-391)Online publication date: 22-Jan-2021
https://doi.org/10.1007/978-3-030-67537-0_23
Tsigkanos CNastic SDustdar S(2019)Towards Resilient Internet of Things: Vision, Challenges, and Research Roadmap2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2019.00174(1754-1764)Online publication date: Jul-2019
https://doi.org/10.1109/ICDCS.2019.00174
Lujic ITruong H(2019)Architecturing Elastic Edge Storage Services for Data-Driven Decision MakingSoftware Architecture10.1007/978-3-030-29983-5_7(97-105)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1007/978-3-030-29983-5_7

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