DaVe: Offloading Delay-Tolerant Data Traffic to Connected Vehicle Networks

Si, Pengbo; He, Yu; Hu, Yao; Yang, Ruifu; Zhang, Yanhua

doi:10.1109/tvt.2016.2550105

Cited by 58 publications

(22 citation statements)

References 39 publications

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“…The cloud-MEC computation offloading problem is formulated through jointly optimizing decision and resource allocation. In [26], a method for effectively utilizing the potential resources of Internet vehicles is proposed to alleviate the congestion problem in other data networks. To further reduce the latency and the transmission cost in the computation offloading, an efficient cloud-based mobile edge computing vehicular network offloading framework is designed through a contract theoretic approach in [27] and [28].…”

Section: Related Workmentioning

confidence: 99%

A Multi-Hop VANETs-Assisted Offloading Strategy in Vehicular Mobile Edge Computing

2020

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Mobile edge computing (MEC) is a suitable solution to improve computational capabilities in vehicular environments, and the computation offloading plays a critical role in MEC. After the computation task generates, in traditional offloading strategies, vehicles offload data only when they have entered the communication range of the MEC server, which greatly increases the time cost and cannot satisfy the delay requirement of certain applications in many cases. To deploy a large number of MEC servers for full coverage of roads is not a realistic solution due to its high construction cost. In this paper, we make full use of the multi-hop vehicular ad hoc networks (VANETs) to assist in computation offloading of vehicles. In the real-time traffic environment, based on the link correlation theory in VANETs, the reliability model of multi-hop routing path is built. Meeting the delay constraints, the optimal offloading strategy with the lowest relaying and computing cost is executed by the binary search algorithm. The simulation results show that the proposed multi-hop VANETs-assisted offloading strategy (MHVA) shows better performance in offloading delay and cost than existing typical strategies under various environments.

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Section: Related Workmentioning

confidence: 99%

A Multi-Hop VANETs-Assisted Offloading Strategy in Vehicular Mobile Edge Computing

2020

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“…Thus, this scheme may not perform well in complex scenarios such as urban roads. To increase the resource utilization efficiency, Si et al [19] explored a new architecture, namely, DaVe, for offloading delay-tolerant data to VANETs. Nevertheless, the offloaded data may suffer from long delays.…”

Section: B Data Offloading Through Vanetsmentioning

confidence: 99%

Stackelberg-Game-Based Mechanism for Opportunistic Data Offloading Using Moving Vehicles

et al. 2019

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Data offloading through vehicular ad hoc networks (VANETs) is one of the most promising methods for overcoming the overload problem in cellular networks. As data delivery by service providers consumes resources such as bandwidth, storage and power, the incentive scheme with the optimal pricing strategy must be identified. In the literature, most incentive schemes focus on offloading through fixed nodes, such as roadside units (RSUs). It remains very challenging to motivate a moving vehicle to help other users deliver their data due to the high mobility of vehicles. Game theory is a widely adopted method for analyzing pricing issues in wireless networks. Therefore, this paper proposes an optimal pricing strategy that uses the Stackelberg game to model the interaction between a service provider and a service requester. Then, the Stackelberg equilibrium is derived under the corresponding conditions. Next, an algorithm is proposed for selecting the service provider that offers the lowest price based on the results of the Stackelberg equilibrium. Finally, the simulation results demonstrate that the proposed algorithm can effectively reduce the downloading time of a task while maximizing the utilities of both the service provider and the requester.

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“…10,11 When to schedule offloaded tasks to other platforms, an ideal offloading approach is indispensable. Currently, most researchers focus on designing variety of effective offloading approaches (eg, mobile data offloading, 8,[12][13][14][15][16][17] computation offloading [18][19][20] for the resource limited mobile devices.…”

Section: Related Workmentioning

confidence: 99%

A WiFi‐aware method for mobile data offloading with deadline constraints

Tang

et al. 2019

Concurrency and Computation

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With an increasing number of public WiFi hotspots have been constructed in metropolitan areas, citizens can leverage these WiFi hotspots to surf the Internet with their smart devices almost everywhere. Compared to cellular networks, most people prefer using WiFi because this can not only save money by reducing the cellular data traffic but also save energy to prolong the battery lifetime of mobile devices. Mobile offloading techniques give the opportunity for smart devices to offload cellular data traffic to WiFi networks whenever they are connected WiFi networks. Although offloading to WiFi networks can cause communication delay, many delay-tolerant applications still prefer doing so in order to save the cellular data traffic. Existing offloading approaches only take the application delay tolerance into consideration and therefore easy to induce some tasks missing deadlines. In this paper, we propose a novel WiFi-aware method for mobile data offloading through WiFi networks with deadline constraints. Specifically, it takes the WiFi distribution in city areas into consideration while making offloading decision. The simulation results on real-world data have shown that our method improves the percentage of tasks that can meet their deadlines, and reduces the average task completion time by comparing with other outstanding methods.

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DaVe: Offloading Delay-Tolerant Data Traffic to Connected Vehicle Networks

Cited by 58 publications

References 39 publications

A Multi-Hop VANETs-Assisted Offloading Strategy in Vehicular Mobile Edge Computing

A Multi-Hop VANETs-Assisted Offloading Strategy in Vehicular Mobile Edge Computing

Stackelberg-Game-Based Mechanism for Opportunistic Data Offloading Using Moving Vehicles

A WiFi‐aware method for mobile data offloading with deadline constraints

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