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Authors: Shelernaz Azimi 1 ; Claus Pahl 1 and Mirsaeid Hosseini Shirvani 2

Affiliations: 1 Free University of Bozen-Bolzano, Bolzano, Italy ; 2 Department of Computer Engineering, Sari branch, Islamic Azad University, Sari, Iran

Keyword(s): Internet of Things, Edge Computing, Cloud Computing, Particle Swarm Optimization, PSO, Performance.

Abstract: Edge computing extends cloud computing capabilities to the edge of the network, allowing for instance Internet-of-Things (IoT) applications to process computation more locally and thus more efficiently. We aim to minimize latency and delay in edge architectures. We focus on an advanced architectural setting that takes communication and processing delays into account in addition to an actual request execution time in a performance engineering scenario. Our architecture is based on multi-cluster edge layer with local independent edge node clusters. We argue that particle swarm optimisation as a bio-inspired optimisation approach is an ideal candidate for distributed load processing in semi-autonomous edge clusters for IoT management. By designing a controller and using a particle swarm optimization algorithm, we can demonstrate that processing and propagation delay and the end-to-end latency (i.e., total response time) can be optimized.

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Paper citation in several formats:
Azimi, S.; Pahl, C. and Shirvani, M. (2020). Particle Swarm Optimization for Performance Management in Multi-cluster IoT Edge Architectures. In Proceedings of the 10th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-424-4; ISSN 2184-5042, SciTePress, pages 328-337. DOI: 10.5220/0009391203280337

@conference{closer20,
author={Shelernaz Azimi. and Claus Pahl. and Mirsaeid Hosseini Shirvani.},
title={Particle Swarm Optimization for Performance Management in Multi-cluster IoT Edge Architectures},
booktitle={Proceedings of the 10th International Conference on Cloud Computing and Services Science - CLOSER},
year={2020},
pages={328-337},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009391203280337},
isbn={978-989-758-424-4},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Cloud Computing and Services Science - CLOSER
TI - Particle Swarm Optimization for Performance Management in Multi-cluster IoT Edge Architectures
SN - 978-989-758-424-4
IS - 2184-5042
AU - Azimi, S.
AU - Pahl, C.
AU - Shirvani, M.
PY - 2020
SP - 328
EP - 337
DO - 10.5220/0009391203280337
PB - SciTePress