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Link to original content: https://doi.org/10.48550/arXiv.2204.05995
[2204.05995] Communication and Computation Assisted Sensing Information Freshness Performance Analysis in Vehicular Networks
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Computer Science > Networking and Internet Architecture

arXiv:2204.05995 (cs)
[Submitted on 12 Apr 2022]

Title:Communication and Computation Assisted Sensing Information Freshness Performance Analysis in Vehicular Networks

Authors:Ning Jiang, Shi Yan, Zhuohan Liu, Chunjing Hu, Mugen Peng
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Abstract:The timely sharing of raw sensing information in the vehicular networks (VNETs) is essential to safety. In order to improve the freshness of sensing information, joint scheduling of multi-dimensional resources such as communication and computation is required. However, the complex relevance among multi-dimensional resources is still unclear, and it is difficult to achieve efficient resource utilization. In this paper, we present a theoretical analysis for a novel metric Age of Information (AoI) on a communication and computation assisted spatial-temporal model. An uplink VNETs scenario where Road Side Units (RSUs) are deployed with computational resource is considered. The transmission and computation process is unified into a two-stage tandem queue and the expression of the average AoI is derived. The network interference is analyzed by modeling the VNETs as Cox Poisson Point Process based on stochastic geometry and the closed-form solution of the coverage probability and the expected data rate performance under the constraints of transmission resources is obtained. The simulation results reveal the basic relationship between communication and computation capacity and show that communication and computation should reach a tradeoff to improve resource utilization while ensuring real-time information requirement.
Subjects: Networking and Internet Architecture (cs.NI)
Cite as: arXiv:2204.05995 [cs.NI]
  (or arXiv:2204.05995v1 [cs.NI] for this version)
  https://doi.org/10.48550/arXiv.2204.05995

Submission history

From: Ning Jiang [view email]
[v1] Tue, 12 Apr 2022 08:57:41 UTC (2,605 KB)
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