Abstract
Fast-response communication is crucial for Vehicular Ad Hoc Network (VANET). In practice, the conventional VANETs, suffering from the high mobility of the vehicles and the ever-growing data to percept and process, cannot meet the demand of fast response currently. In this paper, we study the Dimensioning and Layout Planning (DLP) problem under 5G-based Vehicular Edge Computing Network (VECN) architecture which integrates the 5G Micro Base Station (gNB) and Edge Computing (EC) to reduce the response time. The DLP problem aims to minimize the total placement cost under the constraint of the full coverage. This paper formulates the DLP problem as an integer linear program (ILP) and then proposes a Greedy Algorithm (GA) and a Cost-Effective Heuristic Algorithm (CEHA) toimprove the computation efficiency. The case studies have verified the feasibility and scalability of the DLP formulation and showed that the proposed CEHA is fairly effective and efficient to solve the DLP problem.
Highlights
As a vital component of the Intelligent Transportation System (ITS), Vehicular Ad Hoc Network (VANET) has immersed itself in all walks of life to form an indivisible part of the new Information Age [1]–[5]
Though the architecture integrating gNB and Edge Computing (EC) has become a hot topic in VANETs field (e.g., Khan et al [2] focused on analyzing and comparing the traditional architecture and proposed architecture),due to the high mobility of VANETs, the high cost of the entities, the limited computing resources and so on, it is really necessary to study the dimensioning and layout planning tasks to better place the architecture in the real world
The proposed Greedy Algorithm (GA) could reduce the computation time efficiently, but it is inclined to be trapped in the local optima
Summary
As a vital component of the Intelligent Transportation System (ITS), Vehicular Ad Hoc Network (VANET) has immersed itself in all walks of life to form an indivisible part of the new Information Age [1]–[5]. Considering the case when a user drives amid dense fog, the neighbor vehicles or local status could not be observed,but all the vehicles couldrely on the surrounding vehicles or the RSUs which could transmit the real-time dynamic information (e.g., the speed of surrounding vehicles, accidents and road status) to help avoid traffic collision It is a very complex issue due to the fast changing network topology, diverse road types, vehicle’s high mobility and extremely huge volume of vehicular data. In a nutshell, studying the Dimensioning and Layout Planning (DLP) problem under VECN architecture to generate the optimal practicable layout solution is really necessary The contributions of this paprerTahriesspuampmerarinizveedstaigsaftoelsloawns.optimization framework for the DLP problem of VECN, which integrates the gNB and ECP to improvefast-response and high-bandwidth r communications.
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