Contribution to the design of VANET routing protocols for realistic urban environments

One of the main concerns of the cities' administration is mobility management. In Intelligent Transportation Systems (ITS), pedestrians, vehicles and public transportation systems could share information and react to any situation in the city. The information sensed by vehicles could be useful for other vehicles and for the mobility authorities. Vehicular Ad hoc Networks (VANETs) make possible the communication between vehicles (V2I) and also between vehicles and fixed infrastructure (V2I) managed by the city's authorities. In addition, VANET routing protocols minimize the use of fixed infrastructure since they employ multi-hop V2V communication to reach reporting access points of the city. This thesis aims to contribute in the design of VANET routing protocols to enable reporting services (e.g., vehicular traffic notifications) in urban environments. The first step to achieve this global objective has been the study of components and tools to mimic a realistic VANET scenario. Moreover, we have analyzed the impact of the realism of each one of those components in the simulation results. Then, we have improved the Address Resolution procedure in VANETs by including it in the routing signaling messages. Our approach simplifies the VANET operation and increases the packet delivery ratio as consequence. Afterwards, we have tackled the issue of having duplicate packets in unicast communications and we have proposed routing filters to lower their presence. This way we have been able to increase the available bandwidth and reduce the average packet delay with a slight increase of the packet losses. Besides, we have proposed a Multi-Metric Map aware routing protocol (MMMR) that incorporates four routing metrics (distance, trajectory, vehicle density and available bandwidth) to take the forwarding decisions. With the aim of increasing the number of delivered packets in MMMR, we have developed a Geographical Heuristic Routing (GHR) algorithm. GHR integrates Tabu and Simulated Annealing heuristic optimization techniques to adapt its behavior to the specific scenario characteristics. GHR is generic because it could use any geographical routing protocol to take the forwarding decisions. Additionally, we have designed an easy to implement forwarding strategy based on an extended topology information area of two hops, called 2-hops Geographical Anycast Routing (2hGAR) protocol. Results show that controlled randomness introduced by GHR improves the default operation of MMMR. On the other hand, 2hGAR presents lower delays than GHR and higher packet delivery ratio, especially in high density scenarios. Finally, we have proposed two mixed (integer and linear) optimization models to detect the best positions in the city to locate the Road Side Units (RSUs) which are in charge of gathering all the reporting information generated by vehicles.Una de las principales preocupaciones en la administración de las ciudades es la gestión de la movilidad de sus vehículos, debido a los problemas de tráfico como atascos y accidentes. En los sistemas inteligentes de transporte (SIT), peatones, vehículos y transporte público podrán compartir información y adaptarse a cualquier situación que suceda en la ciudad. La información obtenida por los sensores de los vehículos puede ser útil para otros vehículos y para las autoridades de movilidad. Las redes ad hoc vehiculares (VANETs) hacen posible la comunicación entre los propios vehículos (V2V) y entre vehículos y la infraestructura fija de la red de la ciudad (V2I). Asimismo, los protocolos de encaminamiento para redes vehiculares minimizan el uso de infraestructura fija de red, ya que los protocolos de encaminamiento VANET emplean comunicaciones multisalto entre vehículos para encaminar los mensajes hasta los puntos de acceso de la red en la ciudad. El objetivo de esta tesis doctoral es contribuir en el diseño de protocolos de encaminamiento en redes ad hoc vehiculares para servicios de notificaciones (p.ej. reportes del estado del tráfico) en entornos urbanos. El primer paso para alcanzar este objetivo general ha sido el estudio de componentes y herramientas para simular un escenario realista de red ad hoc vehicular. Además, se ha analizado el impacto del nivel de realismo de cada uno de los componentes de simulación en los resultados obtenidos. Así también, se ha propuesto un mecanismo de resolución de direcciones automático y coherente para redes VANET a través del uso de los propios mensajes de señalización de los protocolos de encaminamiento. Esta mejora simplifica la operación de una red ad hoc vehicular y como consecuencia aumenta la tasa de recepción de paquetes. A continuación, se ha abordado el problema de la aparición inesperada de paquetes de datos duplicados en una comunicación punto a punto. Para ello, se ha propuesto el filtrado de paquetes duplicados a nivel del protocolo de encaminamiento. Esto ha producido un incremento del ancho disponible en el canal y una reducción del retardo medio en la trasmisión de un paquete, a costa de un mínimo aumento de la pérdida de paquetes. Por otra parte, hemos propuesto un protocolo de encaminamiento multi-métrica MMMR (Multi-Metric Map-aware Routing protocol), el cual incorpora cuatro métricas (distancia al destino, trayectoria, densidad de vehículos y ancho de banda) en las decisiones de encaminamiento. Con el objetivo de aumentar la tasa de entrega de paquetes en MMMR, hemos desarrollado un algoritmo heurístico de encaminamiento geográfico denominado GHR (Geographical Heuristic Routing). Esta propuesta integra las técnicas de optimización Tabu y Simulated Annealing, que permiten a GHR adaptarse a las características específicas del escenario. Adicionalmente, hemos propuesto 2hGAR (2-hops Geographical Anycast Routing), un protocolo de encaminamiento anycast que emplea información de la topología de red a dos saltos de distancia para tomar la decisión de encaminamiento de los mensajes. Los resultados muestran que la aleatoriedad controlada de GHR en su operación mejora el rendimiento de MMMR. Asimismo, 2hGAR presenta retardos de paquete menores a los obtenidos por GHR y una mayor tasa de paquetes entregados, especialmente en escenarios con alta densidad de vehículos. Finalmente, se han propuesto dos modelos de optimización mixtos (enteros y lineales) para detectar los mejores lugares de la ciudad donde ubicar los puntos de acceso de la red, los cuales se encargan de recolectar los reportes generados por los vehículos.Postprint (published version

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

An Effective Wireless Sensor Network Routing Protocol Based on Particle Swarm Optimization Algorithm

Improving wireless communication and artificial intelligence technologies by using Internet of Things (Itoh) paradigm has been contributed in developing a wide range of different applications. However, the exponential growth of smart phones and Internet of Things (IoT) devices in wireless sensor networks (WSNs) is becoming an emerging challenge that adds some limitations on Quality of Service (QoS) requirements. End-to-end latency, energy consumption, and packet loss during transmission are the main QoS requirements that could be affected by increasing the number of IoT applications connected through WSNs. To address these limitations, an effective routing protocol needs to be designed for boosting the performance of WSNs and QoS metrics. In this paper, an optimization approach using Particle Swarm Optimization (PSO) algorithm is proposed to develop a multipath protocol, called a Particle Swarm Optimization Routing Protocol (MPSORP). The MPSORP is used for WSN-based IoT applications with a large volume of traffic loads and unfairness in network flow. For evaluating the developed protocol, an experiment is conducted using NS-2 simulator with different configurations and parameters. Furthermore, the performance of MPSORP is compared with AODV and DSDV routing protocols. The experimental results of this comparison demonstrated that the proposed approach achieves several advantages such as saving energy, low end-to-end delay, high packet delivery ratio, high throughput, and low normalization load.publishedVersio

A Scalable Routing Method for Irregular Mobile Ad Hoc Networks

We designed the terminode routing protoc ol with the objective to scale in large mobile ad hoc networks where the topology, or node distribution, is irregular. Our routing protocol is a combination of two protocols: Terminode Local Routing (TLR - to reach a close destination) and Terminode Remot e Routing (TRR - to send data to remote destinations). TRR is the key element to achieve scalability and reduce dependence on intermediate systems. Termin-ode routing uses anchored paths, a list of geographic points - that are not affected by nodes mobili ty -, rather than conventional paths of nodes. Terminode routing is completed by a low-overhead distributed method for discovering of anchored paths, and by a method for handling the inaccuracy of the location information. The presented simu-lation result s confirm that terminode routing performs well in different sized networks. In smaller ad hoc networks performance of terminode routing is comparable to MANET routing protocols. In larger networks, where MANET-like routing protocols break, terminode routing performs well; moreover, in larger networks that are not uniformly populated with nodes, terminode routing outperforms the existing location-based routing protocols

Modeling and simulation of routing protocol for ad hoc networks combining queuing network analysis and ANT colony algorithms

The field of Mobile Ad hoc Networks (MANETs) has gained an important part of the interest of researchers and become very popular in last few years. MANETs can operate without fixed infrastructure and can survive rapid changes in the network topology. They can be studied formally as graphs in which the set of edges varies in time. The main method for evaluating the performance of MANETs is simulation. Our thesis presents a new adaptive and dynamic routing algorithm for MANETs inspired by the Ant Colony Optimization (ACO) algorithms in combination with network delay analysis. Ant colony optimization algorithms have all been inspired by a specific foraging behavior of ant colonies which are able to find, if not the shortest, at least a very good path connecting the colony’s nest with a source of food. Our evaluation of MANETs is based on the evaluation of the mean End-to-End delay to send a packet from source to destination node through a MANET. We evaluated the mean End-to-End delay as one of the most important performance evaluation metrics in computer networks. Finally, we evaluate our proposed ant algorithm by a comparative study with respect to one of the famous On-Demand (reactive) routing protocols called Ad hoc On-Demand Distance Vector (AODV) protocol. The evaluation shows that, the ant algorithm provides a better performance by reducing the mean End-to-End delay than the AODV algorithm. We investigated various simulation scenarios with different node density and pause times. Our new algorithm gives good results under certain conditions such as, increasing the pause time and decreasing node density. The scenarios that are applied for evaluating our routing algorithm have the following assumptions: 2-D rectangular area, no obstacles, bi-directional links, fixed number of nodes operate for the whole simulation time and nodes movements are performed according to the Random Waypoint Mobility (RWM) or the Boundless Simulation Area Mobility (BSAM) model. KEYWORDS: Ant Colony Optimization (ACO), Mobile Ad hoc Network (MANET), Queuing Network Analysis, Routing Algorithms, Mobility Models, Hybrid Simulation

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Wireless Sensor Network Clustering with Machine Learning

Wireless sensor networks (WSNs) are useful in situations where a low-cost network needs to be set up quickly and no fixed network infrastructure exists. Typical applications are for military exercises and emergency rescue operations. Due to the nature of a wireless network, there is no fixed routing or intrusion detection and these tasks must be done by the individual network nodes. The nodes of a WSN are mobile devices and rely on battery power to function. Due the limited power resources available to the devices and the tasks each node must perform, methods to decrease the overall power consumption of WSN nodes are an active research area. This research investigated using genetic algorithms and graph algorithms to determine a clustering arrangement of wireless nodes that would reduce WSN power consumption and thereby prolong the lifetime of the network. The WSN nodes were partitioned into clusters and a node elected from each cluster to act as a cluster head. The cluster head managed routing tasks for the cluster, thereby reducing the overall WSN power usage. The clustering configuration was determined via genetic algorithm and graph algorithms. The fitness function for the genetic algorithm was based on the energy used by the nodes. It was found that the genetic algorithm was able to cluster the nodes in a near-optimal configuration for energy efficiency. Chromosome repair was also developed and implemented. Two different repair methods were found to be successful in producing near-optimal solutions and reducing the time to reach the solution versus a standard genetic algorithm. It was also found the repair methods were able to implement gateway nodes and energy balance to further reduce network energy consumption

The Application of Ant Colony Optimization

The application of advanced analytics in science and technology is rapidly expanding, and developing optimization technics is critical to this expansion. Instead of relying on dated procedures, researchers can reap greater rewards by utilizing cutting-edge optimization techniques like population-based metaheuristic models, which can quickly generate a solution with acceptable quality. Ant Colony Optimization (ACO) is one the most critical and widely used models among heuristics and meta-heuristics. This book discusses ACO applications in Hybrid Electric Vehicles (HEVs), multi-robot systems, wireless multi-hop networks, and preventive, predictive maintenance