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MobiCache: a mobility-aware caching technique in vehicular edge computing

Published: 14 October 2022 Publication History

Abstract

Vehicular edge computing (VEC) brings computational resources at the edge of vehicular networks (VANETs). In VEC, the roadside unit (RSU) across the road segment acts as an edge server. The vehicle having less computational capability offloads high computation tasks to its nearby RSU for processing. There is a significant energy consumption occurs at the RSU in computing each high computation task. To minimize the energy consumption, a caching technique is used at RSUs. The greatest challenge of caching in VEC is the mobility of vehicles. In this poster, we propose a Mobility-Aware Caching technique (MobiCache) in VEC. MobiCache uses an actor-critic deep reinforcement learning framework to find the best routes for migrating the popular cache contents of RSUs according to the mobility pattern of vehicles. Simulation results show that our proposed caching strategy reduces the energy consumption by an average of 39.54% as compared to other existing caching techniques.

References

[1]
Nam Ky Giang, Victor C.M. Leung, and Rodger Lea. 2016. On Developing Smart Transportation Applications in Fog Computing Paradigm. In Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications (Malta, Malta) (DIVANet '16). 91--98.
[2]
Muzammil Hussain Shahid, Ahmad Raza Hameed, Saif ul Islam, Hasan Ali Khattak, Ikram Ud Din, and Joel J.P.C. Rodrigues. 2020. Energy and delay efficient fog computing using caching mechanism. Computer Communications 154 (2020), 534--541.
[3]
Jingjing Yao and Nirwan Ansari. 2019. Joint Content Placement and Storage Allocation in C-RANs for IoT Sensing Service. IEEE Internet of Things Journal 6, 1 (2019), 1060--1067.
[4]
Jingjing Yao and Nirwan Ansari. 2021. Caching in Dynamic IoT Networks by Deep Reinforcement Learning. IEEE Internet of Things Journal 8, 5 (2021), 3268--3275.
[5]
Zhengxin Yu, Jia Hu, Geyong Min, Zhiwei Zhao, Wang Miao, and M. Shamim Hossain. 2021. Mobility-Aware Proactive Edge Caching for Connected Vehicles Using Federated Learning. IEEE Transactions on Intelligent Transportation Systems 22, 8 (2021), 5341--5351.

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cover image ACM Conferences
MobiCom '22: Proceedings of the 28th Annual International Conference on Mobile Computing And Networking
October 2022
932 pages
ISBN:9781450391818
DOI:10.1145/3495243
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 October 2022

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Author Tags

  1. computation offloading
  2. computational caching
  3. energy optimization
  4. vehicular edge computing

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