IoV Scenario: Implementation of a Bandwidth Aware Algorithm in Wireless Network Communication Mode
| Autor: | Neeraj Kumar, Chao Wang, Mohsen Guizani, Peiying Zhang, Gagangeet Singh Aujla |
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| Rok vydání: | 2020 |
| Předmět: |
Networking and Internet Architecture (cs.NI)
FOS: Computer and information sciences Network architecture bandwidth requirement Computer Science - Artificial Intelligence Computer Networks and Communications Computer science Wireless network business.industry Aerospace Engineering Particle swarm optimization BA-VNE Algorithm Computer Science - Networking and Internet Architecture Artificial Intelligence (cs.AI) wireless network communication Automotive Engineering Bandwidth (computing) Resource allocation Wireless The Internet Electrical and Electronic Engineering virtual network embedding business Virtual network Algorithm |
| Zdroj: | IEEE Transactions on Vehicular Technology. 69:15774-15785 |
| ISSN: | 1939-9359 0018-9545 |
| DOI: | 10.1109/tvt.2020.3035341 |
| Popis: | Wireless network communication has developed rapidly in recent years, especially in the field of Internet of vehicles (IoV). However, due to the limitations of traditional network architecture, resource scheduling in wireless network environment is still facing great challenges. We focus on the urgent need of users for bandwidth resources in the IoV scenario under virtual network environment. This paper proposes a bandwidth aware multi domain virtual network embedding (BA-VNE) algorithm. The algorithm is mainly aimed at the problem that users need a lot of bandwidth in wireless communication mode, and solves the problem of bandwidth resource allocation from the perspective of virtual network embedding (VNE). In order to improve the performance of the algorithm, we introduce particle swarm optimization (PSO) algorithm to optimize the performance of the algorithm. In order to verify the effectiveness of the algorithm, we have carried out simulation experiments from link bandwidth, mapping cost and virtual network request (VNR) acceptance rate. The final results show that the proposed algorithm is better than other representative algorithms in the above indicators. This work was supported in part by the Major Scientific and Technological Projects of CNPC under Grant ZD2019-183-006, and in part by “the Fundamental Research Funds for the Central Universities” of China University of Petroleum (East China) under Grants 20CX05017 A and 18CX02139 A. The review of this article was coordinated by Prof. Jelena Misic. (Corresponding authors: Neeraj Kumar and Peiying Zhang.) Peiying Zhang and Chao Wang are with the College of Computer Science and Technology, China University of Petroleum (East China), Qingdao 266580, P. R., China |
| Databáze: | OpenAIRE |
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