An Edge Caching Scheme to Distribute Content in Vehicular Networks

Su, Zhou; Hui, Yilong; Xu, Qiuliang; Yang, Tingting; Liu, Jianyi; Jia, Yunjian

doi:10.1109/tvt.2018.2824345

Cited by 160 publications

(60 citation statements)

References 46 publications

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“…In the proposed work, we assume that vehicles download interesting contents from a given library

scriptF = false{1, …, F false}

, where all contents are of equal size of L ( f ) bits and differing popularities.The probability content − f ( f =1,…, F ) being downloaded is denoted by P i ( f ) and i ( i = l , r ); different sides of the highway have different popularities. In fact, the popularity of downloaded contents follows Zipf's distribution, which can be expressed as

\begin{matrix} alignleft \\ align-1 P_{i} (f) & align-2 = \frac{Ω_{i}}{f^{α_{i}}}, \\ align-1 where Ω_{i} & align-2 = {(\sum_{j}^{F} \frac{1}{j^{α_{i}}})}^{- 1} . \end{matrix}

Parameter α in (7) describes the steepness of the distribution. As the distribution of contents in the content delivery network servers and the data traffic dynamics of the mobile terminal, this type of power law is used to characterize many real‐world phenomena .…”

Section: System Modelmentioning

confidence: 99%

Caching mechanism for mobile edge computing in V2I networks

Luo

Liwang

Huang

et al. 2019

Trans Emerging Tel Tech

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The caching-enabled mobile edge computing (MEC) system becomes increasingly crucial to the future long-term evolution vehicle-to-infrastructure (LTE-V2I) network, especially for fast delivery of popular content of delay-sensitive applications in the backhaul capacity-limited vehicular networks. Most related studies mainly focus on computation offloading strategy design and coding caching, while the deployment strategy design of caching capacities for high-speed vehicles has been overlooked. In this paper, we investigate the deployment problem in LTE-V2I networks with particular consideration on high-speed vehicles. First, in a one-way scenario, a joint optimization framework is formulated to minimize the cache size of the MEC system, meanwhile maximizing the average downloading percentage, where the MEC system's backhaul capacities, vehicle speeds, content popularity distributions, and sides of the highway are taken into account. The impacts of LTE-V2I system parameters, eg, vehicle speed, on the objective function are revealed through the one-way optimization. Then, the two-way optimization is formulated and solved by developing an iterative optimization approach based on the aforementioned one-way scenario. Particularly, the optimal caching allocation between two ways is derived. Simulation results validate the effectiveness of the proposed approaches even with low backhaul capacities and high vehicle speed.

show abstract

“…In the proposed work, we assume that vehicles download interesting contents from a given library

scriptF = false{1, …, F false}

\begin{matrix} alignleft \\ align-1 P_{i} (f) & align-2 = \frac{Ω_{i}}{f^{α_{i}}}, \\ align-1 where Ω_{i} & align-2 = {(\sum_{j}^{F} \frac{1}{j^{α_{i}}})}^{- 1} . \end{matrix}

Section: System Modelmentioning

confidence: 99%

Caching mechanism for mobile edge computing in V2I networks

Luo

Liwang

Huang

et al. 2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…This should be appropriately determined by an optimization tool, such as geometric programming optimization, etc. A caching [ 19 , 20 , 21 ] based UAV relay will be investigated where queuing theory should be employed to analyze the performance of the WSN system. …”

Section: Research Direction and Conclusionmentioning

confidence: 99%

UAV Based Relay for Wireless Sensor Networks in 5G Systems

Fu¹,

Zhao²,

Su³

et al. 2018

Sensors

Self Cite

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Relay is one of the most significant issues in smart industrial wireless sensor networks (WSN) due to the low transmitting power of sensors. By relay, the signals of sensors can be concentrated at the relay and further transmitted to the base station for decreasing energy consumption in the system. In the past decades, the relay in WSN is generally one super sensor with large transmitting power. However, the placement of the super sensor is static, which leads to the instability of performance in WSN under the time-varying wireless environment. Fortunately, unmanned aerial vehicles (UAV) can provide an effective leverage to improve the environment-adaptation in WSN compared to the static relay in WSN. In this paper, we employ UAV as the relay in WSN, which can move in three-dimensional space to possess a better position to minimize the system power consumption. We use a simple case study to demonstrate the effectiveness of UAV in WSN. Extended simulations are also given to verify the preferable performance of the UAV based relay in WSN.

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“…Hui et al 5 proposed a fog computing-based resolution framework to efficiently resolve the individuals identity. Su et al 6 developed an edge caching scheme in vehicular networks based on edge computing. Tang et al 7 designed a hierarchical distributed fog computing architecture to support data-intensive analysis in future smart cities.…”

Section: Introductionmentioning

confidence: 99%

Mobile edge computing resource allocation: A joint Stackelberg game and matching strategy

Guo

Xing

Dong³

et al. 2019

International Journal of Distributed Sensor Networks

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Mobile edge computing has attracted great interests in the popularity of fifth-generation (5G) networks and Internet of Things. It aims to supply low-latency and high-interaction services for delay-sensitive applications. Utilizing mobile edge computing with Smart Home, which is one of the most important fields of Internet of Things, is a method to satisfy users’ demand for higher computing power and storage capacity. However, due to limited computing resource, how to improve efficiency of resource allocation is a challenge. In this article, we propose a hierarchical architecture in Smart Home with mobile edge computing, providing low-latency services and promoting edge process for smart devices. Based on that, a Stackelberg Game is designed in order to allocate computing resource to devices efficiently. Then, one-to-many matching is established to handle resource allocation problems. It is proved that the allocation strategy can optimize the utility of mobile edge computing server and improve allocating efficiency. Simulation results show the effectiveness of the proposed strategy compared with schemes based on auction game, and present performance with different changing system parameters.

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An Edge Caching Scheme to Distribute Content in Vehicular Networks

Cited by 160 publications

References 46 publications

Caching mechanism for mobile edge computing in V2I networks

Caching mechanism for mobile edge computing in V2I networks

UAV Based Relay for Wireless Sensor Networks in 5G Systems

Mobile edge computing resource allocation: A joint Stackelberg game and matching strategy

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