Cost-Effective Resource Sharing in an Internet of Vehicles-Employed Mobile Edge Computing Environment

By bringing the computation and storage resources close proximity to the mobile network edge, mobile edge computing (MEC) is a key enabling technology for satisfying the Internet of Vehicles (IoV) infotainment applications’ requirements, e.g., video streaming service (VSA). However, the explosive gr...

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Veröffentlicht in:Symmetry (Basel) Jg. 10; H. 11; S. 594
Hauptverfasser: Nguyen, Tri D. T., Nguyen, Tien-Dung, Nguyen, Van Dung, Pham, Xuan-Qui, Huh, Eui-Nam
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 05.11.2018
Schlagworte:
Cost control
Edge computing
Internet of Vehicles
Mixed integer
Mobile computing
Nonlinear programming
Quality of service
Streaming media
Traffic speed
Vehicles
Video transmission
Volunteers
Wireless communications
Wireless networks
ISSN:2073-8994, 2073-8994
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Zusammenfassung:By bringing the computation and storage resources close proximity to the mobile network edge, mobile edge computing (MEC) is a key enabling technology for satisfying the Internet of Vehicles (IoV) infotainment applications’ requirements, e.g., video streaming service (VSA). However, the explosive growth of mobile video traffic brings challenges for video streaming providers (VSPs). One known issue is that a huge traffic burden on the vehicular network leads to increasing VSP costs for providing VSA to mobile users (i.e., autonomous vehicles). To address this issue, an efficient resource sharing scheme between underutilized vehicular resources is a promising solution to reduce the cost of serving VSA in the vehicular network. Therefore, we propose a new VSA model based on the lower cost of obtaining data from vehicles and then minimize the VSP’s cost. By using existing data resources from nearby vehicles, our proposal can reduce the cost of providing video service to mobile users. Specifically, we formulate our problem as mixed integer nonlinear programming (MINP) in order to calculate the total payment of the VSP. In addition, we introduce an incentive mechanism to encourage users to rent its resources. Our solution represents a strategy to optimize the VSP serving cost under the quality of service (QoS) requirements. Simulation results demonstrate that our proposed mechanism is possible to achieve up to 21% and 11% cost-savings in terms of the request arrival rate and vehicle speed, in comparison with other existing schemes, respectively.
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ISSN:2073-8994
2073-8994
DOI:10.3390/sym10110594