Journal
PEER-TO-PEER NETWORKING AND APPLICATIONS
Volume 12, Issue 6, Pages 1550-1574Publisher
SPRINGER
DOI: 10.1007/s12083-019-00752-0
Keywords
Internet of things; Unmanned aerial vehicles; Code dissemination; Multi-objective optimization; Cost
Funding
- National Natural Science Foundation of China [61772554]
- Natural Science Foundation of Zhejiang Province [LY17F020032]
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With the rapid development of software-defined technologies, emerging multimedia applications are booming, which require real-time communication and computation via devices. Meanwhile, the program codes in multimedia applications need to be updated periodically to accommodate changes in the edge networking environment. Therefore, a huge number of smart sensing devices which are deployed in the infrastructures of smart city can play a bigger role than ever before due to their program codes in multimedia applications can be updated by sensing data. However, how to spread program codes to a large amount of devices which are distributed in smart city in a low-cost and fast way is a challenging issue. To solve the issue, in this paper, an Unmanned Aerial Vehicles (UAVs) joint Vehicles as Data Mules for Fast Codes Dissemination (UVDCD) scheme is proposed to spread codes as a fast and low-cost pattern for edge networking in smart city. In UVDCD scheme, first of all, large amount of vehicles in smart city act as mules for code dissemination. Although the cost of the method is low and can quickly cover most networks, there is a very long trailing phenomenon for this approach, i.e. in the early stage of code dissemination, the code dissemination rate increases rapidly over time and have a high efficiency, but after a short time, the increase of code dissemination rate has become very slowly over time. So, in this situation, the unmanned aerial vehicle is used to spread the program codes of intelligent devices where vehicles are hard to spread, thereby eliminating the trailing phenomenon in code dissemination. In order to achieve a high dissemination efficiency for UAV, first, we cluster the device nodes which have not received codes, then we select the optimized UAV flight trajectory based on the cluster so that the total length of the UAV flight path is the shortest, i.e. low-cost, and the number of devices which can receive codes is the largest. Finally, the validity of UVDCD scheme is confirmed based on real vehicle data, and through experiments, it can effectively overcome the trailing phenomenon in code dissemination after using UAV. The coverage ratio and dissemination speed are higher than those of previous strategies and increase 2.11% and 69.44% respectively.
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