Improving the Routing Layer of Ad Hoc Networks Through Prediction Techniques

Cada dia és més evident el paper clau que juguen la informàtica/computació mòbil i les tecnologies sense fils a les nostres activitats diàries. Estar sempre connectat, en qualsevol moment i lloc, és actualment més una necessitat que un luxe. Els escenaris de computació ubics creats en base a aquests avenços tecnològics, permeten a les persones proporcionar i consumir informació compartida. En aquests escenaris, les xarxes que donen suport a aquestes comunicacions són típicament sense fils i ad hoc. Les característiques dinàmiques i canviants de les xarxes ad hoc, fan que el treball realitzat per la capa d'enrutament tingui un gran impacte en el rendiment d'aquestes xarxes. És molt important que la capa d'enrutament reaccioni ràpidament als canvis que es produeixen, i fins i tot s'avanci als que es produiran en un futur proper, mitjançant l'aplicació de tècniques de predicció. Aquesta tesi investiga si les tècniques de predicció poden millorar la capa d'enrutament de les xarxes ad hoc. Com a primer pas en aquesta direcció, explorem la potencialitat d'una estratègia de Predictor-Basat-en-Història (HBP) per predir la Informació de Control Topològic (TCI) generada pels protocols d'enrutament. Demostrem que hi ha una gran oportunitat per predir TCI, i aquesta predicció pot centrar-se en un petit subconjunt de missatges. En base a les nostres troballes, implementem el predictor OLSR-HBP i l'avaluem respecte al protocol Optimized Link State Routing (OLSR). OLSR-HBP aconsegueix disminucions importants de TCI (sobrecàrrega de senyalització), sense afectar el funcionament de la xarxa i necessita una quantitat de recursos petita i assequible. Finalment, en referència a l'impacte de la predicció en les dades d'enrutament tant de la informació de Qualitat d'Enllaç como de Ruta (o Extrem-a-Extrem), demostrem que l'Anàlisi de Sèries Temporals és un enfocament prometedor per predir amb precisió, tant la Qualitat d'Enllaç como la Qualitat d'Extrem a Extrem en Xarxes Comunitàries.Cada día es más evidente el papel clave que juegan la informática/computación móvil y las tecnologías inalámbricas en nuestras actividades diarias. Estar siempre conectado, en cualquier momento y lugar, es actualmente más una necesidad que un lujo. Los escenarios de computación ubicuos creados en base a estos avances tecnológicos, permiten a las personas proporcionar y consumir información compartida. En estos escenarios, las redes que dan soporte a estas comunicaciones son típicamente inalámbricas y ad hoc. Las características dinámicas y cambiantes de las redes ad hoc, hacen que el trabajo realizado por la capa de enrutamiento tenga un gran impacto en el rendimiento de estas redes. Es muy importante que la capa de enrutamiento reaccione rápidamente a los cambios que se producen, e incluso se adelante a los que sucederán en un futuro cercano, mediante la aplicación de técnicas de predicción. Esta tesis investiga si las técnicas de predicción pueden mejorar la capa de enrutamiento de las redes ad hoc. Como primer paso en esta dirección, exploramos la potencialidad de una estrategia de Predictor-Basado-en-Historia (HBP) para predecir la Información de Control Topológico (TCI) generada por los protocolos de enrutamiento. Demostramos que hay una gran oportunidad para predecir TCI, y esta predicción puede centrarse en un pequeño subconjunto de mensajes. En base a nuestros hallazgos, implementamos el predictor OLSR-HBP y lo evaluamos con respecto al protocolo Optimized Link State Routing (OLSR). OLSR-HBP consigue disminuciones importantes de TCI (sobrecarga de señalización), sin afectar al funcionamiento de la red, y necesita una cantidad de recursos pequeña y asequible. Finalmente, en referencia al impacto de la predicción en los datos de enrutamiento tanto de la información de Calidad de Enlace como de Ruta (o Extremo-a-Extremo), demostramos que el Análisis de Series Temporales es un enfoque prometedor para predecir con precisión, tanto la Calidad de Enlace como la Calidad de Extremo a Extremo en Redes Comunitarias.Everyday becomes more evident the key role that mobile computing and wireless technologies play in our daily activities. Being always connected, anytime, and anywhere is today more a necessity than a luxury. The ubiquitous computing scenarios created based on these technology advances allow people to provide and consume shared information. In these scenarios, the supporting communication networks are typically wireless and ad hoc. The dynamic and changing characteristics of the ad hoc networks, makes the work done by the routing layer to have a high impact on the performance of these networks. It is very important for the routing layer to quickly react to changes that happen, and even be advanced to what will happen in the near future, by applying prediction techniques. This thesis investigates whether prediction techniques can improve the routing layer of ad hoc networks. As a first step in this direction, in this thesis we explored the potentiality of a History-Based Predictor (HBP) strategy to predict the Topology Control Information (TCI) generated by routing protocols. We demonstrated that there is a high opportunity for predicting theTCI, and this prediction can be just focused on a small subset of messages. Based on our findings we implemented the OLSR-HBP predictor and evaluated it with regard to the Optimized Link State Routing (OLSR) protocol. OLSR History-Based Predictor (OLSR-HBP) achieved important decreases of TCI (signaling overhead), without disturbing the network operation, and requiring a small and affordable amount of resources. Finally, regarding the impact of Prediction on the routing data for both Link and Path (or End-to-End) Quality information, we demonstrated that Time-series analysis is a promising approach to accurately predict both Link and End-to-End Quality in Community Networks

Formulations and identification of algorithmic solutions for enabling opportunistic networks - M4.1

Milestone M4.1 del projecte Europeu OneFIT (ICT-2009-257385).This document contains a detailed description of the algorithms to be implemented to manage the opportunistic networks. There are defined according to the functional and system architecture (WP2) to fulfil the technical challenges. These algorithms will implemented during the WP4.2 and validated during the WP4.3Postprint (published version

Synoptic analysis techniques for intrusion detection in wireless networks

Current system administrators are missing intrusion alerts hidden by large numbers of false positives. Rather than accumulation more data to identify true alerts, we propose an intrusion detection tool that e?ectively uses select data to provide a picture of ?network health?. Our hypothesis is that by utilizing the data available at both the node and cooperative network levels we can create a synoptic picture of the network providing indications of many intrusions or other network issues. Our major contribution is to provide a revolutionary way to analyze node and network data for patterns, dependence, and e?ects that indicate network issues. We collect node and network data, combine and manipulate it, and tease out information about the state of the network. We present a method based on utilizing the number of packets sent, number of packets received, node reliability, route reliability, and entropy to develop a synoptic picture of the network health in the presence of a sinkhole and a HELLO Flood attacker. This method conserves network throughput and node energy by requiring no additional control messages to be sent between the nodes unless an attacker is suspected. We intend to show that, although the concept of an intrusion detection system is not revolutionary, the method in which we analyze the data for clues about network intrusion and performance is highly innovative

Optimising routing and trustworthiness of ad hoc networks using swarm intelligence

This thesis was submitted for the degree of Doctor of Philsophy and awarded by Brunel UniversityThis thesis proposes different approaches to address routing and security of MANETs using swarm technology. The mobility and infrastructure-less of MANET as well as nodes misbehavior compose great challenges to routing and security protocols of such a network. The first approach addresses the problem of channel assignment in multichannel ad hoc networks with limited number of interfaces, where stable route are more preferred to be selected. The channel selection is based on link quality between the nodes. Geographical information is used with mapping algorithm in order to estimate and predict the links’ quality and routes life time, which is combined with Ant Colony Optimization (ACO) algorithm to find most stable route with high data rate. As a result, a better utilization of the channels is performed where the throughput increased up to 74% over ASAR protocol. A new smart data packet routing protocol is developed based on the River Formation Dynamics (RFD) algorithm. The RFD algorithm is a subset of swarm intelligence which mimics how rivers are created in nature. The protocol is a distributed swarm learning approach where data packets are smart enough to guide themselves through best available route in the network. The learning information is distributed throughout the nodes of the network. This information can be used and updated by successive data packets in order to maintain and find better routes. Data packets act like swarm agents (drops) where they carry their path information and update routing information without the need for backward agents. These data packets modify the routing information based on different network metrics. As a result, data packet can guide themselves through better routes. In the second approach, a hybrid ACO and RFD smart data packet routing protocol is developed where the protocol tries to find shortest path that is less congested to the destination. Simulation results show throughput improvement by 30% over AODV protocol and 13% over AntHocNet. Both delay and jitter have been improved more than 96% over AODV protocol. In order to overcome the problem of source routing introduced due to the use of the ACO algorithm, a solely RFD based distance vector protocol has been developed as a third approach. Moreover, the protocol separates reactive learned information from proactive learned information to add more reliability to data routing. To minimize the power consumption introduced due to the hybrid nature of the RFD routing protocol, a forth approach has been developed. This protocol tackles the problem of power consumption and adds packets delivery power minimization to the protocol based on RFD algorithm. Finally, a security model based on reputation and trust is added to the smart data packet protocol in order to detect misbehaving nodes. A trust system has been built based on the privilege offered by the RFD algorithm, where drops are always moving from higher altitude to lower one. Moreover, the distributed and undefined nature of the ad hoc network forces the nodes to obligate to cooperative behaviour in order not to be exposed. This system can easily and quickly detect misbehaving nodes according to altitude difference between active intermediate nodes

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks