Combinatorial Channel Signature Modulation for Wireless ad-hoc Networks

In this paper we introduce a novel modulation and multiplexing method which facilitates highly efficient and simultaneous communication between multiple terminals in wireless ad-hoc networks. We term this method Combinatorial Channel Signature Modulation (CCSM). The CCSM method is particularly efficient in situations where communicating nodes operate in highly time dispersive environments. This is all achieved with a minimal MAC layer overhead, since all users are allowed to transmit and receive at the same time/frequency (full simultaneous duplex). The CCSM method has its roots in sparse modelling and the receiver is based on compressive sampling techniques. Towards this end, we develop a new low complexity algorithm termed Group Subspace Pursuit. Our analysis suggests that CCSM at least doubles the throughput when compared to the state-of-the art.Comment: 6 pages, 7 figures, to appear in IEEE International Conference on Communications ICC 201

Adaptive search in mobile peer-to-peer databases

Information is stored in a plurality of mobile peers. The peers communicate in a peer to peer fashion, using a short-range wireless network. Occasionally, a peer initiates a search for information in the peer to peer network by issuing a query. Queries and pieces of information, called reports, are transmitted among peers that are within a transmission range. For each search additional peers are utilized, wherein these additional peers search and relay information on behalf of the originator of the search

Privacy-Preserving Distributed Optimization via Subspace Perturbation: A General Framework

As the modern world becomes increasingly digitized and interconnected, distributed signal processing has proven to be effective in processing its large volume of data. However, a main challenge limiting the broad use of distributed signal processing techniques is the issue of privacy in handling sensitive data. To address this privacy issue, we propose a novel yet general subspace perturbation method for privacy-preserving distributed optimization, which allows each node to obtain the desired solution while protecting its private data. In particular, we show that the dual variables introduced in each distributed optimizer will not converge in a certain subspace determined by the graph topology. Additionally, the optimization variable is ensured to converge to the desired solution, because it is orthogonal to this non-convergent subspace. We therefore propose to insert noise in the non-convergent subspace through the dual variable such that the private data are protected, and the accuracy of the desired solution is completely unaffected. Moreover, the proposed method is shown to be secure under two widely-used adversary models: passive and eavesdropping. Furthermore, we consider several distributed optimizers such as ADMM and PDMM to demonstrate the general applicability of the proposed method. Finally, we test the performance through a set of applications. Numerical tests indicate that the proposed method is superior to existing methods in terms of several parameters like estimated accuracy, privacy level, communication cost and convergence rate

DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment

Networking - A Statistical Physics Perspective

Efficient networking has a substantial economic and societal impact in a broad range of areas including transportation systems, wired and wireless communications and a range of Internet applications. As transportation and communication networks become increasingly more complex, the ever increasing demand for congestion control, higher traffic capacity, quality of service, robustness and reduced energy consumption require new tools and methods to meet these conflicting requirements. The new methodology should serve for gaining better understanding of the properties of networking systems at the macroscopic level, as well as for the development of new principled optimization and management algorithms at the microscopic level. Methods of statistical physics seem best placed to provide new approaches as they have been developed specifically to deal with non-linear large scale systems. This paper aims at presenting an overview of tools and methods that have been developed within the statistical physics community and that can be readily applied to address the emerging problems in networking. These include diffusion processes, methods from disordered systems and polymer physics, probabilistic inference, which have direct relevance to network routing, file and frequency distribution, the exploration of network structures and vulnerability, and various other practical networking applications.Comment: (Review article) 71 pages, 14 figure

Flexible Application-Layer Multicast in Heterogeneous Networks

This work develops a set of peer-to-peer-based protocols and extensions in order to provide Internet-wide group communication. The focus is put to the question how different access technologies can be integrated in order to face the growing traffic load problem. Thereby, protocols are developed that allow autonomous adaptation to the current network situation on the one hand and the integration of WiFi domains where applicable on the other hand

Integrated Architecture for Configuration and Service Management in MANET Environments

Esta tesis nos ha permitido trasladar algunos conceptos teóricos de la computación ubicua a escenarios reales, identificando las necesidades específicas de diferentes tipos de aplicaciones. Con el fin de alcanzar este objetivo, proponemos dos prototipos que proporcionan servicios sensibles al contexto en diferentes entornos, tales como conferencias o salas de recuperación en hospitales. Estos prototipos experimentales explotan la tecnología Bluetooth para ofrecer información basada en las preferencias del usuario. En ambos casos, hemos llevado a cabo algunos experimentos con el fin de evaluar el comportamiento de los sistemas y su rendimento. También abordamos en esta tesis el problema de la autoconfiguración de redes MANET basadas en el estándar 802.11 a través de dos soluciones novedosas. La primera es una solución centralizada que se basa en la tecnología Bluetooth, mientras la segunda es una solución distribuida que no necesita recurrir a ninguna tecnología adicional, ya que se basa en el uso del parámetro SSID. Ambos métodos se han diseñado para permitir que usuarios no expertos puedan unirse a una red MANET de forma transparente, proporcionando una configuración automática, rápida, y fiable de los terminales. Los resultados experimentales en implementaciones reales nos han permitido evaluar el rendimiento de las soluciones propuestas y demostrar que las estaciones cercanas se pueden configurar en pocos segundos. Además, hemos comparado ambas soluciones entre sí para poner de manifiesto las diferentes ventajas y desventajas en cuanto a rendimento. La principal contribución de esta tesis es EasyMANET, una plataforma ampliable y configurable cuyo objetivo es automatizar lo máximo posible las tareas que afectan a la configuración y puesta en marcha de redes MANET, de modo que su uso sea más simple y accesible.Cano Reyes, J. (2012). Integrated Architecture for Configuration and Service Management in MANET Environments [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/14675Palanci