Adaptive Quality-of-Service-Based Routing for Vehicular Ad Hoc Networks With Ant Colony Optimization

• Published in: IEEE transactions on vehicular technology Vol. 66; no. 4; pp. 3249 - 3264
• Main Authors: Guangyu Li, Boukhatem, Lila, Jinsong Wu
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Ant colony optimization; Ant colony optimization (ACO); Computer Science; Computer simulation; Intersections; Mobile ad hoc networks; Packets (communication); Protocol (computers); Quality of service; quality of service (QoS); Quality of service architectures; Roads; Route selection; Routing; routing protocol; Routing protocols; Vehicle dynamics; Vehicles; Vehicular ad hoc networks; vehicular ad hoc networks (VANETs); Roads; Vehicular ad hoc networks; Quality of service; Routing; Routing protocols; Vehicle dynamics; Vehicles
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2016.2586382

Developing highly efficient routing protocols for vehicular ad hoc networks (VANETs) is a challenging task, mainly due to the special characters of such networks: large-scale sizes, frequent link disconnections, and rapid topology changes. In this paper, we propose an adaptive quality-of-service (QoS)-based routing for VANETs called AQRV. This new routing protocol adaptively chooses the intersections through which data packets pass to reach the destination, and the selected route should satisfy the QoS constraints and fulfil the best QoS in terms of three metrics, namely connectivity probability, packet delivery ratio (PDR), and delay. To achieve the given objectives, we mathematically formulate the routing selection issue as a constrained optimization problem and propose an ant colony optimization (ACO)-based algorithm to solve this problem. In addition, a terminal intersection (TI) concept is presented to decrease routing exploration time and alleviate network congestion. Moreover, to decrease network overhead, we propose local QoS models (LQMs) to estimate real time and complete QoS of urban road segments. Simulation results validate our derived LQM models and show the effectiveness of AQRV.