Achieving Small World Properties using Bio-Inspired Techniques in Wireless Networks

It is highly desirable and challenging for a wireless ad hoc network to have self-organization properties in order to achieve network wide characteristics. Studies have shown that Small World properties, primarily low average path length and high clustering coefficient, are desired properties for networks in general. However, due to the spatial nature of the wireless networks, achieving small world properties remains highly challenging. Studies also show that, wireless ad hoc networks with small world properties show a degree distribution that lies between geometric and power law. In this paper, we show that in a wireless ad hoc network with non-uniform node density with only local information, we can significantly reduce the average path length and retain the clustering coefficient. To achieve our goal, our algorithm first identifies logical regions using Lateral Inhibition technique, then identifies the nodes that beamform and finally the beam properties using Flocking. We use Lateral Inhibition and Flocking because they enable us to use local state information as opposed to other techniques. We support our work with simulation results and analysis, which show that a reduction of up to 40% can be achieved for a high-density network. We also show the effect of hopcount used to create regions on average path length, clustering coefficient and connectivity.Comment: Accepted for publication: Special Issue on Security and Performance of Networks and Clouds (The Computer Journal

Roteamento de tráfego veicular colaborativo e sem infraestrutura para sistemas de transportes inteligentes

Orientadores: Leandro Aparecido Villas, Edmundo Roberto Mauro MadeiraTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Devido à atual tendência mundial de urbanização, a sociedade moderna enfrenta, cada vez mais, sérios problemas de mobilidade urbana. Além disso, com o aumento constante do fluxo de tráfego veicular, as atuais soluções existentes para gerenciamento de tráfego se tornaram ineficientes. Com isso, para atender às crescentes necessidades dos sistemas de transporte, é necessário sistemas de transporte inteligentes (ITS). O desenvolvimento de ITS sustentável requer integração e interoperabilidade contínuas com tecnologias emergentes, tais como as redes veiculares (VANETs). As VANETs são consideradas uma tecnologia promissora que provê aplicações críticas de segurança e serviços de entretenimento, consequentemente melhorando a experiência de viagem do motorista e dos passageiros. Esta tese propõe um sistema de gerenciamento de tráfego de veículos sem a necessidade de uma infraestrutura de apoio. Para alcançar o sistema desejado foram necessários propor soluções intermediárias que contribuíram nesta tese. A primeira contribuição reside em uma solução que emprega conhecimento histórico dos padrões de mobilidade dos motoristas para obter uma visão global da situação da rede viária. Diferentemente de outras abordagens que precisam de troca constante de informações entre os veículos e o servidor central, nossa solução utiliza informações espaciais e temporais sobre padrões de mobilidade, além das informações específicas da infraestrutura viária, a fim de identificar congestionamentos no tráfego, permitindo, assim, o planejamento de roteamento de veículos. Como segunda contribuição, foi proposta uma solução distribuída para calcular a intermediação egocêntrica nas VANETs. Por meio da métrica egocêntrica foi proposto um mecanismo inovador de ranqueamento de veículos em redes altamente dinâmicas. As principais vantagens desse mecanismo para aplicações de VANETs são: (i) a redução do consumo de largura de banda e (ii) a superação do problema de topologias altamente dinâmicas. A terceira contribuição é uma solução de planejamento de rotas colaborativo com intuito de melhorar o gerenciamento do tráfego de veículos em cenários urbanos. Como última contribuição, esta tese integra as soluções descritas acima, propondo um sistema eficiente de gerenciamento de tráfego de veículos. As soluções propostas foram amplamente comparadas com outras soluções da literatura em diferentes métricas de avaliação de desempenho. Os resultados mostram que o sistema de gerenciamento de tráfego de veículos proposto é eficiente e escalável, qual pode ser uma boa alternativa para mitigar os problemas de mobilidade urbanaAbstract: Due to the current global trend of urbanization, modern society is facing severe urban mobility problems. In addition, considering the constant increase in vehicular traffic on roads, existing traffic management solutions have become inefficient. In order to assist the increasing needs of transport systems today, there is a need for intelligent transportation systems (ITS). Developing a sustainable ITS requires seamless integration and interoperability with emerging technologies such as vehicular ad-hoc networks (VANETs). VANETs are considered to be a promising technology providing access to critical life-safety applications and infotainment services, consequently improving drivers¿ and passengers¿ on-road experiences. This thesis proposes an infrastructure-less vehicular traffic management system. To achieve such a system, intermediate solutions that contributed to this thesis were proposed. The first contribution lies in a solution that employs historical knowledge of driver mobility patterns to gain an overall view of the road network situation. Unlike other approaches that need constant information exchange between vehicles and the central server, our solution uses space and temporal information about mobility patterns, as well as road infrastructure information, in order to identify traffic congestion, thus allowing for vehicle routing planning. Secondly, a distributed solution to calculate egocentric betweenness in VANETs was proposed. Through the egocentric metric, an innovative vehicle ranking mechanism in highly dynamic networks was proposed. The main advantages of this mechanism for VANETs applications are (i) reduced bandwidth consumption and (ii) overcoming the problem of highly dynamic topologies. The third contribution is a collaborative route planning solution designed to improve vehicle traffic management in urban settings. As the last contribution, this thesis integrates the solutions described above, proposing an efficient vehicle traffic management system. The proposed solutions were widely compared with other literature solutions on different performance evaluation metrics. The evaluation results show that the proposed vehicle traffic management system is efficient, scalable, and cost-effective, which may be a good alternative to mitigate urban mobility problemsDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação2015/25588-6FAPES

Exploiting vehicular social networks and dynamic clustering to enhance urban mobility management

Transport authorities are employing advanced traffic management system (ATMS) to improve vehicular traffic management efficiency. ATMS currently uses intelligent traffic lights and sensors distributed along the roads to achieve its goals. Furthermore, there are other promising technologies that can be applied more efficiently in place of the abovementioned ones, such as vehicular networks and 5G. In ATMS, the centralized approach to detect congestion and calculate alternative routes is one of the most adopted because of the difficulty of selecting the most appropriate vehicles in highly dynamic networks. The advantage of this approach is that it takes into consideration the scenario to its full extent at every execution. On the other hand, the distributed solution needs to previously segment the entire scenario to select the vehicles. Additionally, such solutions suggest alternative routes in a selfish fashion, which can lead to secondary congestions. These open issues have inspired the proposal of a distributed system of urban mobility management based on a collaborative approach in vehicular social networks (VSNs), named SOPHIA. The VSN paradigm has emerged from the integration of mobile communication devices and their social relationships in the vehicular environment. Therefore, social network analysis (SNA) and social network concepts (SNC) are two approaches that can be explored in VSNs. Our proposed solution adopts both SNA and SNC approaches for alternative route-planning in a collaborative way. Additionally, we used dynamic clustering to select the most appropriate vehicles in a distributed manner. Simulation results confirmed that the combined use of SNA, SNC, and dynamic clustering, in the vehicular environment, have great potential in increasing system scalability as well as improving urban mobility management efficiency1916CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP401802/2016-7; 2015/25588-6; 2016/24454-9; 2018/02204-6; 465446/2014-088887.136422/2017-002014/50937-

Beyond Traditional DTN Routing: Social Networks for Opportunistic Communication

This article examines the evolution of routing protocols for intermittently connected ad hoc networks and discusses the trend toward social-based routing protocols. A survey of current routing solutions is presented, where routing protocols for opportunistic networks are classified based on the network graph employed. The need to capture performance tradeoffs from a multi-objective perspective is highlighted.Comment: 8 pages, 4 figures, 1 tabl

SOCIAL AND LOCATION BASED ROUTING IN DELAY TOLERANT NETWORKS

Delay tolerant networks (DTNs) are a special type of wireless mobile networks which may lack continuous network connectivity. Routing in DTNs is very challenging as it must handle network partitions, long delays, and dynamic topology in such networks. Recently, the consideration of social characteristics of mobile nodes provides a new angle of view in the design of DTNs routing protocols. In many DTNs, a multitude of mobile devices are used and carried by people (e.g. pocket switched networks and vehicular networks), whose behaviors are better described by social models. This opens the new possibilities of social-based routing, in which the knowledge of social characteristics is used for making better forwarding decision. However, the social relations do not necessarily reflect the true device communication opportunities in a dynamic DTN. On the other hand, the increasing availability of location technologies (GPS, GSM networks, etc.) enables mobile devices to obtain their locations easily. Consider that an individual’s location history in the real world implies his/her social interests and behaviors to some extent, in this dissertation, we study new social based DTN routing protocols, which utilize location and/or social features to achieve efficient and stable routing for delay tolerant networks. We first incorporate the location features into the social-based DTN routing methods to improve their performance by treating location similarity among nodes as possible social relationship. Then, we dis- cuss the possibility and methods to further improve routing performance by adding limited amount of throw-boxes into the networks to aid the DTN relay. Several throw-boxes based routing protocols and location selection methods for throw-boxes are proposed. All pro- posed routing methods are evaluated via extensive simulations with real life trace data (such as MIT reality, Nokia MDC, and Orange D4D)

Vers une amélioration de la diffusion des informations dans les réseaux sans-fils

Dans les systèmes d'alertes publiques, l étude de la diffusion des informations dans le réseau est essentielle. Les systèmes de diffusion des messages d'alertes doivent atteindre beaucoup de nœuds en peu de temps. Dans les réseaux de communication basés sur les interactions device to device , on s'est récemment beaucoup intéressé à la diffusion des informations et le besoin d'auto-organisation a été mis en évidence. L'auto-organisation conduit à des comportements locaux et des interactions qui ont un effet sur le réseau global et présentent un avantage de scalabilité. Ces réseaux auto-organisés peuvent être autonomes et utiliser peu d'espace mémoire. On peut développer des caractères auto-organisés dans les réseaux de communication en utilisant des idées venant de phénomènes naturels. Il semble intéressant de chercher à obtenir les propriétés des small world pour améliorer la diffusion des informations dans le réseau. Dans les modèles de small world on réalise un recâblage des liens dans le réseau en changeant la taille et la direction des liens existants. Dans un environnement sans-fils autonome une organisation de ce type peut être créée en utilisant le flocking, l'inhibition latérale et le beamforming . Dans ce but, l'auteur utilise d'abord l'analogie avec l'inhibition latérale, le flocking et le beamforming pour montrer comment la diffusion des informations peut être améliorée. L'analogue de l'inhibition latérale est utilisé pour créer des régions virtuelles dans le réseau. Puis en utilisant l'analogie avec les règles du flocking, on caractérise les propriétés des faisceaux permettant aux nœuds de communiquer dans les régions. Nous prouvons que les propriétés des small world sont vérifiées en utilisant la mesure des moyennes des longueurs des chemins. Cependant l'algorithme proposé est valable pour les réseaux statiques alors que dans les cas introduisant de la mobilité, les concepts d'inhibition latérale et de flocking nécessiteraient beaucoup plus de temps. Dans le cas d'un réseau mobile la structure du réseau change fréquemment. Certaines connexions intermittentes impactent fortement la diffusion des informations. L'auteur utilise le concept de stabilité avec le beamforming pour montrer comment on peut améliorer la diffusion des informations. Dans son algorithme il prévoit d'abord la stabilité du nœud en utilisant des informations locales et il utilise ce résultat pour identifier les nœuds qui réaliseront du beamforming. Dans l'algorithme, les nœuds de stabilité faible sont autorisés à faire du beamforming vers les nœuds de forte stabilité. La frontière entre forte et faible stabilité est fixée par un seuil. Cet algorithme ne nécessite pas une connaissance globale du réseau, mais utilise des données locales. Les résultats sont validés en étudiant le temps au bout duquel plus de nœuds reçoivent l'information et en comparant avec d'autres algorithmes de la littérature. Cependant, dans les réseaux réels, les changements de structure ne sont pas dus qu'à la mobilité, mais également à des changements de la densité des nœuds à un moment donné. Pour tenir compte de l'influence de tels événements sur la diffusion des informations concernant la sécurité publique, l'auteur utilise les concepts de modèle de métapopulation, épidémiologiques, beamforming et mobilité géographique obtenu à partir de données D4D. L'auteur propose la création de trois états latents qu'il ajoute au modèle épidémiologique connu: SIR. L'auteur étudie les états transitoires en analysant l'évolution du nombre de postes ayant reçu les informations et compare les résultats concernant ce nombre dans les différents cas. L'auteur démontre ainsi que le scenario qu'il propose permet d'améliorer le processus de diffusion des informations. Il montre aussi les effets de différents paramètres comme le nombre de sources, le nombre de paquets, les paramètres de mobilité et ceux qui caractérisent les antennes sur la diffusion des informationsIn public warning message systems, information dissemination across the network is a critical aspect that has to be addressed. Dissemination of warning messages should be such that it reaches as many nodes in the network in a short time. In communication networks those based on device to device interactions, dissemination of the information has lately picked up lot of interest and the need for self organization of the network has been brought up. Self organization leads to local behaviors and interactions that have global effects and helps in addressing scaling issues. The use of self organized features allows autonomous behavior with low memory usage. Some examples of self organization phenomenon that are observed in nature are Lateral Inhibition and Flocking. In order to provide self organized features to communication networks, insights from such naturally occurring phenomenon is used. Achieving small world properties is an attractive way to enhance information dissemination across the network. In small world model rewiring of links in the network is performed by altering the length and the direction of the existing links. In an autonomous wireless environment such organization can be achieved using self organized phenomenon like Lateral inhibition and Flocking and beamforming (a concept in communication). Towards this, we first use Lateral Inhibition, analogy to Flocking behavior and beamforming to show how dissemination of information can be enhanced. Lateral Inhibition is used to create virtual regions in the network. Then using the analogy of Flocking rules, beam properties of the nodes in the regions are set. We then prove that small world properties are achieved using average path length metric. However, the proposed algorithm is applicable to static networks and Flocking and Lateral Inhibition concepts, if used in a mobile scenario, will be highly complex in terms of computation and memory. In a mobile scenario such as human mobility aided networks, the network structure changes frequently. In such conditions dissemination of information is highly impacted as new connections are made and old ones are broken. We thus use stability concept in mobile networks with beamforming to show how information dissemination process can be enhanced. In the algorithm, we first predict the stability of a node in the mobile network using locally available information and then uses it to identify beamforming nodes. In the algorithm, the low stability nodes are allowed to beamform towards the nodes with high stability. The difference between high and low stability nodes is based on threshold value. The algorithm is developed such that it does not require any global knowledge about the network and works using only local information. The results are validated using how quickly more number of nodes receive the information and different state of the art algorithms. We also show the effect of various parameters such as number of sources, number of packets, mobility parameters and antenna parameters etc. on the information dissemination process in the network. In realistic scenarios however, the dynamicity in the network is not only related to mobility. Dynamic conditions also arise due to change in density of nodes at a given time. To address effect of such scenario on the dissemination of information related to public safety in a metapopulation, we use the concepts of epidemic model, beamforming and the countrywide mobility pattern extracted from the $D4D$ dataset. Here, we also propose the addition of three latent states to the existing epidemic model ($SIR$ model). We study the transient states towards the evolution of the number of devices having the information and the difference in the number of devices having the information when compared with different cases to evaluate the results. Through the results we show that enhancements in the dissemination process can be achieved in the addressed scenarioEVRY-INT (912282302) / SudocSudocFranceF

Graph-enabled Intelligent Vehicular Network data processing

Intelligent vehicular network (IVN) is the underlying support for the connected vehicles and smart city, but there are several challenges for IVN data processing due to the dynamic structure of the vehicular network. Graph processing, as one of the essential machine learning and big data processing paradigm, which provide a set of big data processing scheme, is well-designed to processing the connected data. In this paper, we discussed the research challenges of IVN data processing and motivated us to address these challenges by using graph processing technologies. We explored the characteristics of the widely used graph algorithms and graph processing frameworks on GPU. Furthermore, we proposed several graph-based optimization technologies for IVN data processing. The experimental results show the graph processing technologies on GPU can archive excellent performance on IVN data

Human dynamic networks in opportunistic routing and epidemiology

Measuring human behavioral patterns has broad application across different sciences. An individual’s social, proximal and geographical contact patterns can have significant importance in Delay Tolerant Networking (DTN) and epidemiological modeling. Recent advances in computer science have not only provided the opportunity to record these behaviors with considerably higher temporal resolution and phenomenological accuracy, but also made it possible to record specific aspects of the behaviors which have been previously difficult to measure. This thesis presents a data collection system using tiny sensors which is capable of recording humans’ proximal contacts and their visiting pattern to a set of geographical locations. The system also collects information on participants’ health status using weekly surveys. The system is tested on a population of 36 participants and 11 high-traffic public places. The resulting dataset offers rich information on human proximal and geographic contact patterns cross-linked with their health information. In addition to the basic analysis of the dataset, the collected data is applied to two different applications. In DTNs the dataset is used to study the importance of public places as relay nodes, and described an algorithm that takes advantage of stationary nodes to improve routing performance and load balancing in the network. In epidemiological modeling, the collected dataset is combined with data on H1N1 infection spread over the same time period and designed a model on H1N1 pathogen transmission based on these data. Using the collected high-resolution contact data as the model’s contact patterns, this work represents the importance of contact density in addition to contact diversity in infection transmission rate. It also shows that the network measurements which are tied to contact duration are more representative of the relation between centrality of a person and their chance of contracting the infection

Supporting cooperation and coordination in open multi-agent systems

Cooperation and coordination between agents are fundamental processes for increasing aggregate and individual benefit in open Multi-Agent Systems (MAS). The increased ubiquity, size, and complexity of open MAS in the modern world has prompted significant research interest in the mechanisms that underlie cooperative and coordinated behaviour. In open MAS, in which agents join and leave freely, we can assume the following properties: (i) there are no centralised authorities, (ii) agent authority is uniform, (iii) agents may be heterogeneously owned and designed, and may consequently have con icting intentions and inconsistent capabilities, and (iv) agents are constrained in interactions by a complex connecting network topology. Developing mechanisms to support cooperative and coordinated behaviour that remain effective under these assumptions remains an open research problem. Two of the major mechanisms by which cooperative and coordinated behaviour can be achieved are (i) trust and reputation, and (ii) norms and conventions. Trust and reputation, which support cooperative and coordinated behaviour through notions of reciprocity, are effective in protecting agents from malicious or selfish individuals, but their capabilities can be affected by a lack of information about potential partners and the impact of the underlying network structure. Regarding conventions and norms, there are still a wide variety of open research problems, including: (i) manipulating which convention or norm a population adopts, (ii) how to exploit knowledge of the underlying network structure to improve mechanism efficacy, and (iii) how conventions might be manipulated in the middle and latter stages of their lifecycle, when they have become established and stable. In this thesis, we address these issues and propose a number of techniques and theoretical advancements that help ensure the robustness and efficiency of these mechanisms in the context of open MAS, and demonstrate new techniques for manipulating convention emergence in large, distributed populations. Specfically, we (i) show that gossiping of reputation information can mitigate the detrimental effects of incomplete information on trust and reputation and reduce the impact of network structure, (ii) propose a new model of conventions that accounts for limitations in existing theories, (iii) show how to manipulate convention emergence using small groups of agents inserted by interested parties, (iv) demonstrate how to learn which locations in a network have the greatest capacity to in uence which convention a population adopts, and (v) show how conventions can be manipulated in the middle and latter stages of the convention lifecycle

Towards efficacy and efficiency in sparse delay tolerant networks

The ubiquitous adoption of portable smart devices has enabled a new way of communication via Delay Tolerant Networks (DTNs), whereby messages are routed by the personal devices carried by ever-moving people. Although a DTN is a type of Mobile Ad Hoc Network (MANET), traditional MANET solutions are ill-equipped to accommodate message delivery in DTNs due to the dynamic and unpredictable nature of people\u27s movements and their spatio-temporal sparsity. More so, such DTNs are susceptible to catastrophic congestion and are inherently chaotic and arduous. This manuscript proposes approaches to handle message delivery in notably sparse DTNs. First, the ChitChat system [69] employs the social interests of individuals participating in a DTN to accurately model multi-hop relationships and to make opportunistic routing decisions for interest-annotated messages. Second, the ChitChat system is hybridized [70] to consider both social context and geographic information for learning the social semantics of locations so as to identify worthwhile routing opportunities to destinations and areas of interest. Network density analyses of five real-world datasets is conducted to identify sparse datasets on which to conduct simulations, finding that commonly-used datasets in past DTN research are notably dense and well connected, and suggests two rarely used datasets are appropriate for research into sparse DTNs. Finally, the Catora system is proposed to address congestive-driven degradation of service in DTNs by accomplishing two simultaneous tasks: (i) expedite the delivery of higher quality messages by uniquely ordering messages for transfer and delivery, and (ii) avoid congestion through strategic buffer management and message removal. Through dataset-driven simulations, these systems are found to outperform the state-of-the-art, with ChitChat facilitating delivery in sparse DTNs and Catora unencumbered by congestive conditions --Abstract, page iv