URLLC-Awared Resource Allocation for Heterogeneous Vehicular Edge Computing

Vehicular edge computing (VEC) is a promising technology to support real-time vehicular applications, where vehicles offload intensive computation tasks to the nearby VEC server for processing. However, the traditional VEC that relies on single communication technology cannot well meet the communication requirement for task offloading, thus the heterogeneous VEC integrating the advantages of dedicated short-range communications (DSRC), millimeter-wave (mmWave) and cellular-based vehicle to infrastructure (C-V2I) is introduced to enhance the communication capacity. The communication resource allocation and computation resource allocation may significantly impact on the ultra-reliable low-latency communication (URLLC) performance and the VEC system utility, in this case, how to do the resource allocations is becoming necessary. In this paper, the authors consider a heterogeneous VEC with multiple communication technologies and various types of tasks, and propose an effective resource allocation policy to minimize the system utility while satisfying the URLLC requirement. The authors first formulate an optimization problem to minimize the system utility under the URLLC constraint which is modeled by the moment generating function (MGF)-based stochastic network calculus (SNC), then the authors present a Lyapunov-guided deep reinforcement learning (DRL) method to convert and solve the optimization problem. Extensive simulation experiments illustrate that the proposed resource allocation approach is effective.

• Record URL:
  • http://dx.doi.org/10.1109/TVT.2024.3370196
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
• Supplemental Notes:
  • IEEE Transactions on Vehicular Technology - Copyright © 2024, IEEE.
• Authors:
  • Wu, Qiong
  • Wang, Wenhua
  • Fan, Pingyi
  • Fan, Qiang
  • Wang, Jiangzhou
  • 0000-0003-0881-3594
  • Letaief, Khaled B
• Publication Date: 2024-8

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 11789-11805
• Serial:
  • IEEE Transactions on Vehicular Technology
  • Volume: 73
  • Issue Number: 8
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 0018-9545
  • Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25

Subject/Index Terms

• TRT Terms: Heterogeneity; Mobile communication systems; Mobile computing; Resource allocation; Vehicle to infrastructure communications
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01930111
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 13 2024 10:33AM