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Cost-Effective and Robust Service Provisioning in Multi-Access Edge Computing
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AI
DOI：10.1109/TPDS.2024.3435929.png)
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Abstract
En 中文
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 cost-effective and robust service provisioning algorithm, 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.
Keywords:
Servers
Resource management
Costs
Robustness
Artificial intelligence
Power system protection
Power system faults
Edge computing
resource allocation
service computing
traffic scheduling
Journal
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6
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5.2K
Citations:
1.1W
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