Ata uhi

Mean Age of Information in Partial Offloading Mobile Edge Computing Networks

I tiakina i:
I whakaputaina i:arXiv.org (Sep 24, 2024), p. n/a
Kaituhi matua: Dong, Ying
Ētahi atu kaituhi: Xiao, Hang, Hu, Haonan, Zhang, Jiliang, Chen, Qianbin, Zhang, Jie
I whakaputaina:
Cornell University Library, arXiv.org
Ngā marau:
Computation offloading
Performance evaluation
Networks
Queuing theory
Edge computing
Mobile computing
Urunga tuihono:Citation/Abstract
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Whakarāpopotonga:The age of information (AoI) performance analysis is essential for evaluating the information freshness in the large-scale mobile edge computing (MEC) networks. This work proposes the earliest analysis of the mean AoI (MAoI) performance of large-scale partial offloading MEC networks. Firstly, we derive and validate the closed-form expressions of MAoI by using queueing theory and stochastic geometry. Based on these expressions, we analyse the effects of computing offloading ratio (COR) and task generation rate (TGR) on the MAoI performance and compare the MAoI performance under the local computing, remote computing, and partial offloading schemes. The results show that by jointly optimising the COR and TGR, the partial offloading scheme outperforms the local and remote computing schemes in terms of the MAoI, which can be improved by up to 51% and 61%, respectively. This encourages the MEC networks to adopt the partial offloading scheme to improve the MAoI performance.
ISSN:2331-8422
Puna:Engineering Database