Towards Hit-Interruption Tradeoff in Vehicular Edge Caching: Algorithm and Analysis

Zhang, Yao; Li, Changle; Luan, Tom H.; Yuen, Chau; Fu, Yuchuan; Wang, Hui; Wu, Weigang

doi:10.1109/tits.2021.3052355

Cited by 11 publications

(5 citation statements)

References 40 publications

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“…Wang and Grace [205] suggested two proactive caching algorithms based on multi-armed bandit learning, using reinforcement learning to predict the next RSU that a vehicle will pass through to achieve proactive caching in vehicular networks. Zhang et al [209] studied the vehicular edge caching challenge in real vehicle scenarios, designing an adaptive caching algorithm to more effectively utilize caching resources, increase caching prediction success rates, and reduce interruptions in caching services. Fu [210] proposed caching update and pricing algorithms, considering the transcoding of various video versions.…”

Section: Cachingmentioning

confidence: 99%

A Survey on Video Streaming for Next-Generation Vehicular Networks

Huang,

Cheng,

Lien

et al. 2024

Electronics

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As assisted driving technology advances and vehicle entertainment systems rapidly develop, future vehicles will become mobile cinemas, where passengers can use various multimedia applications in the car. In recent years, the progress in multimedia technology has given rise to immersive video experiences. In addition to conventional 2D videos, 360° videos are gaining popularity, and volumetric videos, which can offer users a better immersive experience, have been discussed. However, these applications place high demands on network capabilities, leading to a dependence on next-generation wireless communication technology to address network bottlenecks. Therefore, this study provides an exhaustive overview of the latest advancements in video streaming over vehicular networks. First, we introduce related work and background knowledge, and provide an overview of recent developments in vehicular networking and video types. Next, we detail various video processing technologies, including the latest released standards. Detailed explanations are provided for network strategies and wireless communication technologies that can optimize video transmission in vehicular networks, paying special attention to the relevant literature regarding the current development of 6G technology that is applied to vehicle communication. Finally, we proposed future research directions and challenges. Building upon the technologies introduced in this paper and considering diverse applications, we suggest a suitable vehicular network architecture for next-generation video transmission.

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Section: Cachingmentioning

confidence: 99%

A Survey on Video Streaming for Next-Generation Vehicular Networks

Huang,

Cheng,

Lien

et al. 2024

Electronics

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“…Step 2: In this step, we introduce a greedy offline strategy with utility in cache period l denoted by u ′′ (l). At the beginning of cache period l, the greedy offline strategy releases all contents, and performs purchasing and caching in cache period l so as to maximize the ENSP's utility in cache period l. 6 Note that in both greedy offline strategy and modified offline strategy, the ENSP has no cached content at the beginning of each cache period. The greedy offline strategy focuses on utility maximization in the current cache period, while the modified offline strategy follows the offline optimal strategy that focuses on long-term utility maximization over all cache periods.…”

Section: Competitive Ratio Analysismentioning

confidence: 99%

“…Recently, content popularity prediction has been adopted in many caching strategy designs, as information of content popularity can help to increase the cache hit rate. The work in [6] developed an online regression based on the Gaussian process algorithm to make short-term prediction for contents in vehicular edge caching networks. The work in [7] utilized a temporal convolution network and an attention mechanism to learn content popularity patterns for achieving the hit rate maximization.…”

Section: Introductionmentioning

confidence: 99%

Digital twin driven and intelligence enabled content delivery in end-edge-cloud collaborative 5G networks

Yi¹,

Lv²,

Wang³

et al. 2024

Digital Communications and Networks

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“…Network content was modeled as a heterogeneous information network so that network congestion can be significantly alleviated. In order to improve the cache hit rate and to avoid frequent interruption of cache request services, [18] proposed an on-demand adaptive cache scheme which adjusted the replacement time of cached content according to the requests and the popularity of the content. However, the above works only considered V2I communication in edge caching, making them hard to be adopted to IoV scenarios with poor or no MEC coverage.…”

Section: Related Workmentioning

confidence: 99%

Vehicle clustering based edge caching scheme in internet of vehicles

Yang,

Tan,

Xie

et al. 2023

IET Communications

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With the development of mobile edge computing technology, edge caching provides a feasible solution for low‐latency and high‐reliability data forwarding in the Internet of Vehicles (IoV). Due to the limited number and storage capacity of the edge servers, and the limited communication range of a single vehicle, the delay and connection requirements are hard to be satisfied. A vehicle clustering based edge caching scheme is proposed in this paper, aiming at minimizing the content acquisition delay of the requesting vehicles (RVs) within the communication range of the edge servers. After getting the optimal vehicle association results, the minimization of content acquisition delay is transformed into a knapsack problem, which is then solved by a dynamic programming algorithm to obtain the optimal cache decisions. Simulation results show that the proposed scheme reduces task acquisition delay by at least about 100 s and increases the cache hit rate by about 50%, compared with the random cache scheme.

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Towards Hit-Interruption Tradeoff in Vehicular Edge Caching: Algorithm and Analysis

Cited by 11 publications

References 40 publications

A Survey on Video Streaming for Next-Generation Vehicular Networks

A Survey on Video Streaming for Next-Generation Vehicular Networks

Digital twin driven and intelligence enabled content delivery in end-edge-cloud collaborative 5G networks

Vehicle clustering based edge caching scheme in internet of vehicles

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