Jamal Toutouh

Intelligent OLSR Routing Protocol Optimization for VANETs

Recent advances in wireless technologies have given rise to the emergence of vehicular ad hoc networks (VANETs). In such networks, the limited coverage of WiFi and the high mobility of the nodes generate frequent topology changes and network fragmentations. For these reasons, and taking into account that there is no central manager entity, routing packets through the network is a challenging task. Therefore, offering an efficient routing strategy is crucial to the deployment of VANETs. This paper deals with the optimal parameter setting of the optimized link state routing (OLSR), which is a well-known mobile ad hoc network routing protocol, by defining an optimization problem. This way, a series of representative metaheuristic algorithms (particle swarm optimization, differential evolution, genetic algorithm, and simulated annealing) are studied in this paper to find automatically optimal configurations of this routing protocol. In addition, a set of realistic VANET scenarios (based in the city of Málaga) have been defined to accurately evaluate the performance of the network under our automatic OLSR. In the experiments, our tuned OLSR configurations result in better quality of service (QoS) than the standard request for comments (RFC 3626), as well as several human experts, making it amenable for utilization in VANET configurations.

Automatic tuning of communication protocols for vehicular ad hoc networks using metaheuristics

The emerging field of vehicular ad hoc networks (VANETs) deals with a set of communicating vehicles which are able to spontaneously interconnect without any pre-existing infrastructure. In such kind of networks, it is crucial to make an optimal configuration of the communication protocols previously to the final network deployment. This way, a human designer can obtain an optimal QoS of the network beforehand. The problem we consider in this work lies in configuring the File Transfer protocol Configuration (FTC) with the aim of optimizing the transmission time, the number of lost packets, and the amount of data transferred in realistic VANET scenarios. We face the FTC with five representative state-of-the-art optimization techniques and compare their performance. These algorithms are: Particle Swarm Optimization (PSO), Differential Evolution (DE), Genetic Algorithm (GA), Evolutionary Strategy (ES), and Simulated Annealing (SA). For our tests, two typical environment instances of VANETs for Urban and Highway scenarios have been defined. The experiments using ns- 2 (a well-known realistic VANET simulator) reveal that PSO outperforms all the compared algorithms for both studied VANET instances.

Fast energy-aware OLSR routing in VANETs by means of a parallel evolutionary algorithm

This work tackles the problem of reducing the power consumption of the OLSR routing protocol in vehicular networks. Nowadays, energy-aware and green communication protocols are important research topics, specially when deploying wireless mobile networks. This article introduces a fast automatic methodology to search for energy-efficient OLSR configurations by using a parallel evolutionary algorithm. The experimental analysis demonstrates that significant improvements over the standard configuration can be attained in terms of power consumption, with no noteworthy loss in the QoS.

Performance analysis of optimized VANET protocols in real world tests

Vehicular ad hoc networks (VANETs) provide the communications required to deploy Intelligent Transportation Systems (ITS). In the current state of the art in this field there is a lack of studies on real outdoor experiments to validate the new VANETs protocols and applications proposed by designers. In this work we have addressed the definition of a testbed in order to study the performance of the Vehicular Data Transfer Protocol (VDTP) in a real urban VANET. The VDTP protocol has been tested by employing six different parameter settings: one defined by human experts and five automatically optimized by means of metaheuristic algorithms (PSO, DE, GA, ES, and SA). As a result, we have been able to confirm the performance improvements when optimized VDTP configurations are used, validating the results previously obtained through simulation.

Optimizing OLSR in VANETS with differential evolution: a comprehensive study

Recent advances in communication technologies gave rise to the emergence of vehicular ad-hoc networks (VANETs). Due to the limitations of the wireless technologies used in such networks, designing routing protocols for VANETs is becoming a major concern. One way of obtaining new routing protocols is to modify existing MANET ones adapting them to vehicular environments. It is also important to accurately evaluate these new protocols before using them to deploy VANETs and one way to do this is through simulation. In this work, we assess OLSR and DE-OLSR. For this task, we have carried out a set of simulations over 36 different VANET scenarios based on real data of Málaga (Spain) using IEEE 802.11p definition and considering different urban areas sizes, traffic densities, and workloads. The QoS has been measured using four metrics: PDR, NRL, E2ED, and RPL. This comprehensive performance evaluation shows that DE-OLSR is better-suited for VANETs than the standard version, improving its resource consumption and scalability.

An efficient routing protocol for green communications in vehicular ad-hoc networks

Vehicular ad-hoc networks (VANETs) provide the communications required to deploy Intelligent Transportation Systems (ITS). In the current state of the art there is a lack of studies on Green Communications (energy-efficiency) in VANETs. However, due to the possible interaction with devices that are fed with different electrical sources and the proliferation of electrical vehicles, the power consumption by the wireless communications might become a major concern in VANET design. In this paper, we study the energy-efficiency of a quality-of-service optimized version of OLSR by means of Differential Evolution (DE-OLSR). We have conducted a series of VANET simulations aiming at analyzing the power consumption and the QoS in order to compare DE-OLSR with the standard version of OLSR. An extensive performance evaluation shows that DE-OLSR clearly outperforms the standard version in terms of energy consumption, while offering a competitive QoS.

Parallel Swarm Intelligence for VANETs Optimization

Parallel metaheuristics can enhance and speed up the resolution of hard-to-solve optimization problems by taking advantage of the available processing power. in this study, we present a parallel swarm intelligent method, pPSO, that uses the master-slave paradigm to evaluate all the particles simultaneously over several processing elements. We have applied pPSO to tackle the AODV routing optimization in VANETs, a problem that requires large computation times to evaluate the fitness function. in turn, we apply parallelism for the comprehensive validation of solutions in the simulation analysis. the AODV configuration optimized by pPSO shows the best trade-off among several QoS metrics when compared against state of the art configurations. Our pPSO achieved an average computational efficiency of 86%.

Accuracy and Efficiency in Simulating VANETs

The evaluation of new communication protocols for Vehicular Ad-hoc Networks (VANETs) is a hot topic in research. An efficient design and actual deployment of such software tools is crucial for any VANET. The design phase is difficult and often relies on computer simulation. The later evaluation of protocols in real VANETs is complex due to many difficulties concerning the availability of resources, accurate performance analysis, and reproducible results. Simulation is the most widely solution to make a good design but it presents also an important challenge: the fidelity of the simulation compared to the real results. In this article we measure the differences between the simulation versus the real results with actual moving cars in order to quantify the accuracy of the VANET simulations inside the European CARLINK Project. After a thorough revision of the state of the art, we here go for an analysis of JANE and VanetMobiSim/ns-2, two simulation frameworks. Later, we have defined the scenario where both, simulations and real tests, will be carried out. Our results show that JANE is more appropriate for simulating applications, while ns-2 is more accurate in dealing with the underlying mobile communication network.

QoS-Aware Radio Access Technology (RAT) Selection in Hybrid Vehicular Networks

The increasing number of wireless communication technologies and standards bring immense opportunities and challenges to provide seamless connectivity in Hybrid Vehicular Networks (HVNs). HVNs could not only enhance existing applications but could also spur an array of new services. However, due to sheer number of use cases and applications with diverse and stringent QoS performance requirements it is very critical to efficiently decide on which radio access technology (RAT) to select. In this paper a QoS-aware RAT selection algorithm is proposed for HVN. The proposed algorithm switches between IEEE 802.11p based ad hoc network and LTE cellular network by considering network load and application’s QoS requirements. The simulation-based studies show that the proposed RAT selection mechanism results in lower number of Vertical Handovers (VHOs) and significant performance improvements in terms of packet delivery ratio, latency and application-level throughput.

Multi-objective OLSR optimization for VANETs

Vehicular ad hoc networks (VANETs) are infrastructure-less and self-organized networks deployed among vehicles and other road users. Due to the limitations of the wireless technologies used and the rapid topology changes, designing efficient routing protocols for VANETs is becoming a major concern. In this study, we applied a multi-objective optimization metaheuristic, in order to find efficient OLSR parameterizations that improve the QoS of the OLSR RFC and a previous optimized configurations. Our optimized configuration significantly reduces OLSR scalability problems keeping competitive packet delivery rates. The OLSR routing overhead is reduced between 47% and 76% and the delivery times are between 32% and 38% shorter when using our optimized settings.