Data dissemination for green-VANETs communication: an opportunistic optimization approach

Abstract

Purpose This paper aims to predict the traffic and helps to find a solution. Unpredictable traffic leads more vehicles on the road. The result of which is one of the factors that aggravate traffic congestion. Traffic congestion occurs when the available transport resources are less when compared to the number of vehicles that share the resource. As the number of vehicles increases the resources become scarce and congestion is more. Design/methodology/approach The population of the urban areas keeps increasing as the people move toward the cities in search of jobs and a better lifestyle. This leads to an increase in the number of vehicles on the road. However, the transport network, which is accessible to the citizens is less when compared to their demand. Findings The demand for resources is higher than the actual capacity of the roads and the streets. There are some circumstances, which will aggravate traffic congestion. The circumstances can be the road condition (pot holes and road repair), accidents and some natural calamities. Originality/value There is a lot of research being done to predict the traffic and model it to find a solution, which will make the condition better. However, still, it is an open issue. The accuracy of the predictions done is less.

A modified social spider algorithm for an efficient data dissemination in VANET

“…H. Khelifi et al ( 2020 ) designed a named data networking (NDN) to drive the vehicular ad hoc networks for routing and the security mechanism for enhanced communication. D.C et al ( 2020 ) discussed a data dissemination approach for green VANET to increase pollution-less road transportation with hybrid technique. Classifying skin disease and progress expectation of nominal computational efforts and advance of accurate prediction is discussed by J. Tamang et al( 2021 ).…”

Optimal Reservation Volume of Urban Roads Based on Travel Reservation Strategy

“…In equation (13), d ue w represents the travel demand of an ordinary vehicle. Equation (14) ensures that the sum of the fows assigned to paths equals the travel demand, where u ue,w r is the trafc fow on the path r on the OD pair w. ε ue,w r is the reservation section-path relation, which ensures that ordinary vehicles cannot enter the exclusive section of the reservation travel. If no reservation section exists on path r, then ε ue,w r � 1; otherwise, ε ue,w r � 0.…”

“…It does not consider the trafc state of reserved roads, which deviates from the essence of TRS. Terefore, in recent years, scholars have preferred to mine trafc fow data to determine reservation volumes [14]. Menelaou et al [15] replaced the capacity constraint with the density constraint and used infnitesimal perturbation analysis to capture the dynamic change in the critical density value.…”