A Taxonomy for Congestion Control Algorithms in Vehicular Ad Hoc Networks

One of the main criteria in Vehicular Ad hoc Networks (VANETs) that has attracted the researchers' consideration is congestion control. Accordingly, many algorithms have been proposed to alleviate the congestion problem, although it is hard to find an appropriate algorithm for applications and safety messages among them. Safety messages encompass beacons and event-driven messages. Delay and reliability are essential requirements for event-driven messages. In crowded networks where beacon messages are broadcasted at a high number of frequencies by many vehicles, the Control Channel (CCH), which used for beacons sending, will be easily congested. On the other hand, to guarantee the reliability and timely delivery of event-driven messages, having a congestion free control channel is a necessity. Thus, consideration of this study is given to find a solution for the congestion problem in VANETs by taking a comprehensive look at the existent congestion control algorithms. In addition, the taxonomy for congestion control algorithms in VANETs is presented based on three classes, namely, proactive, reactive and hybrid. Finally, we have found the criteria in which fulfill prerequisite of a good congestion control algorithm

Session Initiation Protocol Attacks and Challenges

In recent years, Session Initiation Protocol (SIP) has become widely used in current internet protocols. It is a text-based protocol much like Hyper Text Transport Protocol (HTTP) and Simple Mail Transport Protocol (SMTP). SIP is a strong enough signaling protocol on the internet for establishing, maintaining, and terminating session. In this paper the areas of security and attacks in SIP are discussed. We consider attacks from diverse related perspectives. The authentication schemes are compared, the representative existing solutions are highlighted, and several remaining research challenges are identified. Finally, the taxonomy of SIP threat will be presented

Ant-based vehicle congestion avoidance framework using vehicular networks / Mohammad Reza Jabbarpour Sattari

Over the last decade, vehicle population has dramatically increased all over the world. This large number of vehicles coupled with the limited capacity of the roads and highways lead to heavy traffic congestion. Besides, it gives rise to air pollution, driver frustration, and costs billions of dollars annually in fuel consumption. Although finding a proper solution for vehicle congestion is a necessity, it is still remaining a challenging task due to the dynamic and unpredictable nature of vehicular environments. Building new high-capacity streets can be a solution but it is very costly, time consuming and in most cases, infeasible due to space limitations. However, optimal usage of the existing roads and streets capacity can lessen the congestion problem in large cities at a lower cost. Intelligent Transportation System (ITS) is a newly emerged system that aims to provide innovative services for different modes of transportation and traffic management. Vehicle Traffic Routing System (VTRS) is one of the ITS applications that can be used for efficient utilization of existing roads’ capacity. Previous researches concentrated on using static algorithms to find the shortest path in VTRSs. However, providing a shortest path without considering other factors such as congestion, accidents, obstacles, travel time and speed is not a proper solution for vehicle traffic congestion problem. The efficiency of VTRSs on mitigating the vehicle congestion is challenged by the high dynamicity and quick changes of vehicular environments due to both predictable (recurring) and unpredictable (non-recurring) events. Most of the existing approaches deal with the congestion problem in a reactive manner and recover vehicle congestion implicitly, which is not a sufficient solution due to non-recurring congestion conditions. Moreover, a same path is suggested to drivers by the existing approaches which switches the congestion from one route to another, specifically, in the case of having a significant number of drivers utilizing these systems simultaneously. This research presents a bio-inspired framework, called “Ant-based Vehicle Congestion Avoidance Framework (AVCAF)”, which is a promising way to alleviate vehicle traffic congestion problem while considering the aforementioned drawbacks. AVCAF predicts vehicles’ average travel speed and combines it with travel time, density, distance, map segmentation and layering to reduce congestion as much as possible by finding the least congested shortest paths in order to avoid congestion instead of recovering from it. AVCAF uses alternative paths from the early stages of the routing process. AVCAF collects real-time traffic data through vehicular networks to consider non-recurring congestion conditions in its routing mechanism via ant-based algorithm. The proposed framework is evaluated and validated through simulation environment. Experimental results conducted on three different scenarios (i.e. various vehicle densities, various system usage rates and accident condition) considering average travel time, speed, distance, number of re-routings and number of congested roads as evaluation metrics. The results show that AVCAF outperforms the existing approaches in terms of average travel time, travel speed, number of re-routings and number of congested roads

Dynamic Congestion Control Algorithm for Vehicular Ad-hoc Networks

Vehicular Ad Hoc Network (VANET) has received increased attention from scholars and industries in recent years. Meanwhile, Congestion control remains the major concern for VANET application due to its characteristics such as bandwidth limitation, fast change of topology and lack of central coordination. Researchers have proposed a number of solutions to overcome these challenges and also to reduce congestion in VANET environment. These solutions are based on packet generation rate, transmit power control, utility function, carrier sense threshold or a combination of them. In this paper, the existing congestion control approaches is classified into three main classes, namely, proactive, reactive and hybrid. Besides, we propose and implement an algorithm by which carrier sense (CS) threshold or MaxBeaconingLoad (MBL) value can be assigned dynamically for fine-tuning the Distributed Fair transmits Power Adjustment for VANETs (D-FPAV) congestion control approach. In addition to optimal channel bandwidth usage, the proposed algorithm can be used in any situation considering traffic and non-traffic conditions