Delay Constraint Data Collection Strategy in VANET

doi:10.23940/ijpe.18.10.p11.23542365

Abstract

Abstract:

Real-time navigation, traffic monitoring, broadcasting messages of accidents and entertainment applications require a large number of data sensed by vehicles in the vehicular Ad-hoc networks (VANET). Collection and aggregation of this data is an essential part of implementing these applications. In this paper, we study the maximize aggregation data (MAD) problem in VANET. Based on the idea of greedy algorithm, two different algorithms are proposed to solve the limited communication MAD problem and unlimited communication MAD problem. The core idea of both algorithms is to construct a dynamic routing tree and scheduling the transmission time of each vehicle simultaneously. Real-time traffic information and changeable remaining time are combined to establish the tree. In order to reduce the invalid transmissions, only vehicles that can carry data within the delay constraint or directly forward data to the target node are considered to become relay nodes, aiding in the transmission process of other vehicles. Simulation is performed on the analog trajectories sets, and results show that our proposed algorithms have a higher collection rate compared with other schemes.

Submitted on July 6, 2018; Revised on August 10, 2018; Accepted on September 8, 2018
References: 21

Huanhuan Yang, Zongpu Jia, and Guojun Xie. Delay Constraint Data Collection Strategy in VANET [J]. Int J Performability Eng, 2018, 14(10): 2354-2365.

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