Distributed Probabilistic Caching strategy in VANETs through Named Data Networking

Deng, Gang; Wang, Liwei; Li, Fengchao; Li, Rere

doi:10.1109/infcomw.2016.7562093

Cited by 45 publications

(6 citation statements)

References 5 publications

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“…However, in this scheme, the master node may experience a bottleneck during high network activity. In another approach, distributed probabilistic caching [18] allows each node to make caching decisions independently based on user demands, vehicle importance, and relative motion. A clustering algorithm is utilized to extract information on user demands and preferences, but this may introduce additional overhead to the network.…”

Section: Related Workmentioning

confidence: 99%

QWLCPM: A Method for QoS-Aware Forwarding and Caching Using Simple Weighted Linear Combination and Proximity for Named Data Vehicular Sensor Network

Dhakal,

Sharma

2024

Electronics

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The named data vehicular sensor network (NDVSN) has become an increasingly important area of research because of the increasing demand for data transmission in vehicular networks. In such networks, ensuring the quality of service (QoS) of data transmission is essential. The NDVSN is a mobile ad hoc network that uses vehicles equipped with sensors to collect and disseminate data. QoS is critical in vehicular networks, as the data transmission must be reliable, efficient, and timely to support various applications. This paper proposes a QoS-aware forwarding and caching algorithm for NDVSNs, called QWLCPM (QoS-aware Forwarding and Caching using Weighted Linear Combination and Proximity Method). QWLCPM utilizes a weighted linear combination and proximity method to determine stable nodes and the best next-hop forwarding path based on various metrics, including priority, signal strength, vehicle speed, global positioning system data, and vehicle ID. Additionally, it incorporates a weighted linear combination method for the caching mechanism to store frequently accessed data based on zone ID, stability, and priority. The performance of QWLCPM is evaluated through simulations and compared with other forwarding and caching algorithms. QWLCPM’s efficacy stems from its holistic decision-making process, incorporating spatial and temporal elements for efficient cache management. Zone-based caching, showcased in different scenarios, enhances content delivery by utilizing stable nodes. QWLCPM’s proximity considerations significantly improve cache hits, reduce delay, and optimize hop count, especially in scenarios with sparse traffic. Additionally, its priority-based caching mechanism enhances hit ratios and content diversity, emphasizing QWLCPM’s substantial network-improvement potential in vehicular environments. These findings suggest that QWLCPM has the potential to greatly enhance QoS in NDVSNs and serve as a promising solution for future vehicular sensor networks. Future research could focus on refining the details of its implementation, scalability in larger networks, and conducting real-world trials to validate its performance under dynamic conditions.

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Section: Related Workmentioning

confidence: 99%

QWLCPM: A Method for QoS-Aware Forwarding and Caching Using Simple Weighted Linear Combination and Proximity for Named Data Vehicular Sensor Network

Dhakal,

Sharma

2024

Electronics

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“…Kind Description [10] Cluster construction Construct clusters based on inter-vehicle distances, vehicle heights, and route stability [11] Cluster construction Clusters may be constructed with multi-hop distances [3] Reducing the cache redundancy Cache probability is determined by channel usage [7] Reducing the cache redundancy Cache probability is determined by content similarity and vehicle mobility [8] Reducing the cache redundancy Cache probability is determined by the characteristics of vehicles' mobility…”

Section: Referencementioning

confidence: 99%

“…As for (2), Refs. [3,7,8] suggest that each vehicle make a probabilistic decision on whether to cache content. While this reduces the redundancy of storing identical content in nearby vehicles, it does not completely eliminate it.…”

Section: Introductionmentioning

confidence: 99%

Efficient V2V Communications by Clustering-Based Collaborative Caching

Tokunaga,

Tang

2024

Electronics

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Vehicle-to-vehicle (V2V) communication plays an important role in enabling autonomous driving. However, when multiple vehicles request the same content, like road conditions, delivering it individually by V2V communication can significantly increase traffic volume, potentially causing congestion in the wireless channel. To address this issue, Content-Centric Network (CCN) technology is applied to V2V communication, which improves communication efficiency by exploiting content cached at vehicles. However, previous methods faced the following challenges: (i) vehicles could not use content stored in nearby vehicles outside the communication path, and (ii) redundant caching of the same content occurred at nearby vehicles. To tackle these challenges, this paper proposes a collaborative caching method in which vehicles are grouped into clusters and each cluster has a designated head responsible for managing caches across all vehicles within the cluster. In this way, this method enables vehicles to use the content cached at adjacent vehicles that are not directly on a communication path. In addition, it eliminates redundant caches, allowing a more diverse range of content storage. Extensive simulation results demonstrate that the proposed approach effectively reduces content delivery latency by 33% compared to the method using clusters without cooperative caching and by 19% compared to the ECV+ method.

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“…According to its results, cache memory is reduced with less performance in diversity and content replication. However, the authors introduced DPC using a probabilistic strategy in [49]; this method increased the delay due to lack of collaboration with other nodes. The PCMP work is discussed in [50], where popular contents are cached at only RSU; due to this, the cache hit ratio decreased with low velocity and increased hop count with high velocity.…”

Section: Related Workmentioning

confidence: 99%

“…We evaluate the DCCMS performance using the ndnSIM [52] based on NS-3 [53]. We compare our work with the AlwaysCache [45], Prob(0.5) [48], DPC [49], and PCMP [50]. The overall results show that our proposed method DCCMS is good compared to other methods.…”

Section: Performance Evaluationmentioning

confidence: 99%

Dynamic Cooperative Cache Management Scheme Based on Social and Popular Data in Vehicular Named Data Network

Ashraf

Huang

Raza

et al. 2022

Wireless Communications and Mobile Computing

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Vehicular Named Data Network (VNDN) is considered a strong paradigm to deploy in vehicular applications. In VNDN, each node has its cache, but due to limited cache, it directly affects the performance in a highly dynamic environment, which requires massive and fast content delivery. To reduce these issues, the cooperative caching plays an efficient role in VNDN. Most studies regarding cooperative caching focus on content replacement and caching algorithms and implement these methods in a static environment rather than a dynamic environment. In addition, few existing approaches addressed the cache diversity and latency in VNDN. This paper proposes a Dynamic Cooperative Cache Management Scheme (DCCMS) based on social and popular data, which improves the cache efficiency and implements it in a dynamic environment. We designed a two-level dynamic caching scheme, in which we choose the right caching node that frequently communicates with other nodes, keep the copy of the most popular content, and distribute it with the requester’s node when needed. The main intention of DCCMS is to improve the cache performance in terms of reducing latency, server load, cache hit ratio, average hop count, cache utilization, and diversity. The simulation results show that our proposed DCCMS scheme improves the cache performance than other state-of-the-art approaches.

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Distributed Probabilistic Caching strategy in VANETs through Named Data Networking

Cited by 45 publications

References 5 publications

QWLCPM: A Method for QoS-Aware Forwarding and Caching Using Simple Weighted Linear Combination and Proximity for Named Data Vehicular Sensor Network

QWLCPM: A Method for QoS-Aware Forwarding and Caching Using Simple Weighted Linear Combination and Proximity for Named Data Vehicular Sensor Network

Efficient V2V Communications by Clustering-Based Collaborative Caching

Dynamic Cooperative Cache Management Scheme Based on Social and Popular Data in Vehicular Named Data Network

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