Treffer: Cost-Effective and Robust Service Provisioning in Multi-Access Edge Computing

Title:
Cost-Effective and Robust Service Provisioning in Multi-Access Edge Computing
Source:
Xiang, Z, Zheng, Y, Wang, D, Taheri, J, Zheng, Z & Guo, M 2024, 'Cost-effective and robust service provisioning in multi-access edge computing', IEEE Transactions on Parallel and Distributed Systems, vol. 35, no. 10, pp. 1765-1779. https://doi.org/10.1109/TPDS.2024.3435929
Publisher Information:
Institute of Electrical and Electronics Engineers (IEEE), 2024.
Publication Year:
2024
Document Type:
Fachzeitschrift Article
File Description:
application/pdf
ISSN:
2161-9883
1045-9219
DOI:
10.1109/tpds.2024.3435929
Rights:
IEEE Copyright
CC BY
Accession Number:
edsair.doi.dedup.....690b8611e62de22e3f5a1f74caa1e38b
Database:
OpenAIRE

Weitere Informationen

With the development of multiaccess edge computing (MEC) technology, an increasing number of researchers and developers are deploying their computation-intensive and IO-intensive services (especially AI services) on edge devices. These devices, being close to end users, provide better performance in mobile environments. By constructing a service provisioning system at the network edge, latency is significantly reduced due to short-distance communication with edge servers. However, since the MEC-based service provisioning system is resource-sensitive and the network may be unstable, careful resource allocation and traffic scheduling strategies are essential. This paper investigates and quantifies the cost-effectiveness and robustness of the MEC-based service provisioning system with the applied resource allocation and traffic scheduling strategies. Based on this analysis, a c ost- e ffective and r obust service provisioning a lgorithm, termed CERA , is proposed to minimize deployment costs while maintaining system robustness. Extensive experiments are conducted to compare the proposed approach with well-known baseline algorithms and evaluate factors impacting the results. The findings demonstrate that CERA achieves at least 15.9% better performance than other baseline algorithms across various instances.