Towards Optimizing the Edge-to-Cloud Continuum Resource Allocation

Igor Capeletti, Ariel Goes de Castro, Daniel Temp, Daniel Temp, Paulo Silas Severo de Souza, Arthur Lorenzon, Fábio Rossi, Fábio Rossi, Marcelo Luizelli

2023

Abstract

The IT community has witnessed a transition towards the cooperation of two major paradigms, Cloud Computing and Edge Computing, paving the way to a Cloud Continuum, where computation can be performed at the various network levels. While this model widens the provisioning possibilities, choosing the most cost-efficient processing location is not trivial. In addition, network bottlenecks between end users and computing facilities assigned for carrying out processing can undermine application performance. To overcome this challenge, this paper presents a novel algorithm that leverages a path-aware heuristic approach to opportunistically process application requests on compute devices along the network path. Once intermediate hosts process information, requests are sent back to users, alleviating the demand on the network core and minimizing end-to-end application latency. Simulated experiments demonstrate that our approach outperforms baseline routing strategies by a factor of 24x in terms of network saturation reduction without sacrificing application latency.

Paper Citation

in Harvard Style

Capeletti I., Goes de Castro A., Temp D., Silas Severo de Souza P., Lorenzon A., Rossi F. and Luizelli M. (2023). Towards Optimizing the Edge-to-Cloud Continuum Resource Allocation. In Proceedings of the 13th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-650-7, SciTePress, pages 90-99. DOI: 10.5220/0011995700003488

in Bibtex Style

@conference{closer23,
author={Igor Capeletti and Ariel Goes de Castro and Daniel Temp and Paulo Silas Severo de Souza and Arthur Lorenzon and Fábio Rossi and Marcelo Luizelli},
title={Towards Optimizing the Edge-to-Cloud Continuum Resource Allocation},
booktitle={Proceedings of the 13th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2023},
pages={90-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011995700003488},
isbn={978-989-758-650-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Towards Optimizing the Edge-to-Cloud Continuum Resource Allocation
SN - 978-989-758-650-7
AU - Capeletti I.
AU - Goes de Castro A.
AU - Temp D.
AU - Silas Severo de Souza P.
AU - Lorenzon A.
AU - Rossi F.
AU - Luizelli M.
PY - 2023
SP - 90
EP - 99
DO - 10.5220/0011995700003488
PB - SciTePress