Managing Congestion in Vehicular Networks Using Tabu Search

Abstract

In this era of communication, exponentially growing networks bring a lot of challenges to address for smoother network functionalities. Among them is efficiency in handling packet traffic to avoid and control congestion. A particular case is applicable to Vehicular Ad-hoc Networks, which are known with unbalanced resource utilisation, communication overheads, high transmission delay and least transmission capacity. This paper aims to minimise the delay and jitter for enhancing the Quality of Service (QoS) in Vehicular Adhoc Networks (VANET) using tabu search algorithm with multi-channel allocation capability. We proposed a scheme that prioritises each message considering the basis of message type or its substances, such as crisis, reference point, and administration oriented etc., and uses tabu search for scheduling the transmission of queued messages in order to enhance the efficiency, security, and durability of VANET. A comprehensive simulation is conducted to validate the proposed scheme and to evaluate the performances in comparison with other state-of-the-art approaches.

A comprehensive survey on congestion control techniques and the research challenges on VANET

“…Message scheduling is following a specific mechanism for controlling the congestion which is distributed, the mechanism gives each node in vehicular communication to assign the priority. Also, schedule the packet which is different from one node to another (Ishaq et al, 2018). The main idea behind this approach is the open-loops technique is to prevent congestion control to be occurred based on the priority and schedule of packets.…”

A survey on congestion detection and control in connected vehicles

“…The RSUs and OBUs direct all DSRC connected vehicles to provide on-demand information about the ongoing network traffic such as speed, position, acceleration, braking status, etc. of the neighboring vehicles [109][110][111][112]. Centralized approaches are easier to implement because they incur less overhead in routing connectivity.…”

“…The decentralized or distributed congestion control approach is the default for VANETs. In this approach, there is a set of local controllers distributed in the entire network and each local controller can extract only limited information of beacon message such as speed, concentration, and travel time MOTabu [47,112], Improvised AODV [114], LBV_AODV [115], and CABS [97] are examples of decentralized approaches for congestion control that have been proposed for VANETs. i) Robust congestion control: Robust congestion control scheme is one of the topology-based centralized congestion control approaches that minimizes congestion in the VANETs environment [67,111].…”

“…v) MOTabu: MOTabu is one of the most commonly used dynamic and topology-based decentralized congestion control techniques in VANETs. The MOTabu algorithm for congestion control is based on the current state of the vehicle and uses the following performance metrics: transmission rate, transmission range, delay, and jitter [47,112]. Section 4.1.2 describes the operation of the MOTabu congestion control approach.…”

Distributed and Fair Beacon Power and Beaconing Rate Adaptation Based on Game Theoretic Approach for Connected Vehicles

“…Their objective is to ensure the dependable and punctual delivery of messages to all neighboring nodes within the network. The authors in (Ishaq et al 2018) used the tabu search algorithm with multi-channel allocation capability to reduce the time delay and jitter for improving the quality of service in VANET. In (Li and Huang 2018), the authors introduce a method for adapting beacon rates based on vehicle mobility prediction.…”