Cloud-Assisted Dynamic Content Sharing among Vehicles

Adachi, Yoshiaki; Yamaguchi, Hirozumi; Higashino, Teruo; Umedu, Takaaki

doi:10.1109/cit.2016.49

Cited by 5 publications

(4 citation statements)

References 25 publications

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“…Overall, the future of V2V communication for smart traffic systems is bright, as the technology will continue to evolve and be integrated with other technologies to improve the efficiency, safety, and overall experience of transportation. The integration of V2V communication with other technologies such as V2I, V2N, and V2X and the use of AI [79], ML [12], Cloud [80], and 5G technologies [81], [82], [83] are considered as an opportunity for the improvement of V2V systems for smart traffic systems.…”

Section: Future Perspectives Of V2v Communication For Smart Traffic S...mentioning

confidence: 99%

V2V Communication in Smart Traffic Systems: Current status, challenges and future perspectives

Yogha Bintoro,

SDH Permana,

Ade Syahputra

et al. 2024

processor

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Implementing V2V communication in intelligent traffic systems has been a topic of growing interest due to its potential to improve road safety and traffic flow. However, the widespread adoption of V2V communication in intelligent traffic systems could be enhanced by various challenges, such as infrastructure cost, security, and interoperability. These challenges must be addressed to improve the potential benefits of V2V communication. The problem statement of this study is to examine the potential benefits and challenges of V2V communication in intelligent traffic systems and provide insights into the current state of the art in V2V communication research. The proposed approach is to conduct a literature review of recent research on V2V communication in intelligent traffic systems to identify the potential benefits and challenges of V2V communication and the current state of the art in V2V communication research. The study aims to contribute to the field by comprehensively understanding the implementation of V2V communication in intelligent traffic systems and informing potential future research in this area. V2V communication can improve road safety and traffic flow in intelligent traffic systems. However, more research is needed to address the challenges and develop advanced and cost-effective V2V communication systems.

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Section: Future Perspectives Of V2v Communication For Smart Traffic S...mentioning

confidence: 99%

V2V Communication in Smart Traffic Systems: Current status, challenges and future perspectives

Yogha Bintoro,

SDH Permana,

Ade Syahputra

et al. 2024

processor

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“…An analytical model is proposed to investigate the system performance in terms of providing data services with delay constraints. Adachi et al in [18] proposed a hybrid approach, where vehicular content (e.g., short video clips, sensor data) is shared among vehicles using V2V and V2I communication via cellular network. The main objective of this paper is to reduce high-cost V2I due to traffic volume in wireless network.…”

Section: Related Workmentioning

confidence: 99%

Robust Resource Allocation Using Edge Computing for Vehicle to Infrastructure (V2I) Networks

Kovalenko

Hussain

Semiari

et al. 2019

2019 IEEE 3rd International Conference on Fog and Edge Computing (ICFEC)

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Development of autonomous and self-driving vehicles requires agile and reliable services to manage hazardous road situations. Vehicular Network is the medium that can provide high-quality services for self-driving vehicles. The majority of service requests in Vehicular Networks are delay intolerant (e.g., hazard alerts, lane change warning) and require immediate service. Therefore, Vehicular Networks, and particularly, Vehicleto-Infrastructure (V2I) systems must provide a consistent realtime response to autonomous vehicles. During peak hours or disasters, when a surge of requests arrives at a Base Station, it is challenging for the V2I system to maintain its performance, which can lead to hazardous consequences. Hence, the goal of this research is to develop a V2I system that is robust against uncertain request arrivals. To achieve this goal, we propose to dynamically allocate service requests among Base Stations. We develop an uncertainty-aware resource allocation method for the federated environment that assigns arriving requests to a Base Station so that the likelihood of completing it on-time is maximized. We evaluate the system under various workload conditions and oversubscription levels. Simulation results show that edge federation can improve robustness of the V2I system by reducing the overall service miss rate by up to 45%.

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“…The main idea behind this technology is to use the local storage of mobile devices to store popular contents and deliver them asynchronously to nearby devices through device-to-device (D2D) communications whenever they need it [3], [4]. Follow-up research utilized this technology in the context of connected vehicles as well, namely Cellular Vehicle-to-Everything (C-V2X) communications [5]- [10]. In C-V2X technology, vehicles with the assistance of cellular infrastructure, collaborate to offload Vehicleto-Infrastructure (V2I) traffic using direct Vehicle-to-Vehicle (V2V) links [5], reduce retrieve time [6], [7], improve bandwidth efficiency and enhance data service performance [8], and improve overall service quality and delivery rate by proactively placing relevant data in vehicles' storage [9], [10].…”

Section: Introduction Fmentioning

confidence: 99%

“…Follow-up research utilized this technology in the context of connected vehicles as well, namely Cellular Vehicle-to-Everything (C-V2X) communications [5]- [10]. In C-V2X technology, vehicles with the assistance of cellular infrastructure, collaborate to offload Vehicleto-Infrastructure (V2I) traffic using direct Vehicle-to-Vehicle (V2V) links [5], reduce retrieve time [6], [7], improve bandwidth efficiency and enhance data service performance [8], and improve overall service quality and delivery rate by proactively placing relevant data in vehicles' storage [9], [10]. Another technology for 5G evolution is Full-Duplex (FD) radios, which allows simultaneous transmission and reception on the same time/frequency resources [11].…”

Section: Introduction Fmentioning

confidence: 99%

Probabilistic Analysis of Operating Modes in Cache-Enabled Full-Duplex D2D Networks

Naslcheraghi¹,

Wette²,

Sansò³

2021

Preprint

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With the extensive acquisition of various mobile applications, cellular networks are facing challenges due to exponentially growing demand for high data rate, which causes a great burden on mobile core networks and backhaul links. Cache-enabled Device-to-Device (D2D) communication, which is recognized as one of the key enablers of the fifth generation (5G) cellular network, is a promising solution to alleviate this problem. However, conventional half-duplex (HD) communication may not be sufficient to provide fast enough content delivery over D2D links in order to meet strict latency targets of emerging D2D applications. In-band full-duplex (FD), with its capability of allowing simultaneous transmission and reception, can provide more content delivery opportunities, thus resulting improved spectral efficiency and latency reduction. However, given the random nature of the cached contents in user devices and users' random requests, it is unlikely to consider all involving nodes in content exchange collaborations as a pure HD or FD network. In this paper, we aim to analyze the caching perspective of a finite network of D2D nodes in which each node is endowed with FD capability and utilize a more realistic caching policy. We model and analyze all possible operating modes for an arbitrary device, which we compute the probability of occurrence of each mode along with the Probability Mass Functions (PMFs) of nodes that are operating in all possible modes. Our analysis concretely quantize all possible outcomes that strongly depend on the random nature of the caching parameters, yielding to have an accurate insight on the caching performance and all possible outcomes of the cache-enabled FD-D2D network.

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Cloud-Assisted Dynamic Content Sharing among Vehicles

Cited by 5 publications

References 25 publications

V2V Communication in Smart Traffic Systems: Current status, challenges and future perspectives

V2V Communication in Smart Traffic Systems: Current status, challenges and future perspectives

Robust Resource Allocation Using Edge Computing for Vehicle to Infrastructure (V2I) Networks

Probabilistic Analysis of Operating Modes in Cache-Enabled Full-Duplex D2D Networks

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