Contention techniques for opportunistic communication in wireless mesh networks

Auf dem Gebiet der drahtlosen Kommunikation und insbesondere auf den tieferen Netzwerkschichten sind gewaltige Fortschritte zu verzeichnen. Innovative Konzepte und Technologien auf der physikalischen Schicht (PHY) gehen dabei zeitnah in zelluläre Netze ein. Drahtlose Maschennetzwerke (WMNs) können mit diesem Innovationstempo nicht mithalten. Die Mehrnutzer-Kommunikation ist ein Grundpfeiler vieler angewandter PHY Technologien, die sich in WMNs nur ungenügend auf die etablierte Schichtenarchitektur abbilden lässt. Insbesondere ist das Problem des Scheduling in WMNs inhärent komplex. Erstaunlicherweise ist der Mehrfachzugriff mit Trägerprüfung (CSMA) in WMNs asymptotisch optimal obwohl das Verfahren eine geringe Durchführungskomplexität aufweist. Daher stellt sich die Frage, in welcher Weise das dem CSMA zugrunde liegende Konzept des konkurrierenden Wettbewerbs (engl. Contention) für die Integration innovativer PHY Technologien verwendet werden kann. Opportunistische Kommunikation ist eine Technik, die die inhärenten Besonderheiten des drahtlosen Kanals ausnutzt. In der vorliegenden Dissertation werden CSMA-basierte Protokolle für die opportunistische Kommunikation in WMNs entwickelt und evaluiert. Es werden dabei opportunistisches Routing (OR) im zustandslosen Kanal und opportunistisches Scheduling (OS) im zustandsbehafteten Kanal betrachtet. Ziel ist es, den Durchsatz von elastischen Paketflüssen gerecht zu maximieren. Es werden Modelle für Überlastkontrolle, Routing und konkurrenzbasierte opportunistische Kommunikation vorgestellt. Am Beispiel von IEEE 802.11 wird illustriert, wie der schichtübergreifende Entwurf in einem Netzwerksimulator prototypisch implementiert werden kann. Auf Grundlage der Evaluationsresultate kann der Schluss gezogen werden, dass die opportunistische Kommunikation konkurrenzbasiert realisierbar ist. Darüber hinaus steigern die vorgestellten Protokolle den Durchsatz im Vergleich zu etablierten Lösungen wie etwa DCF, DSR, ExOR, RBAR und ETT.In the field of wireless communication, a tremendous progress can be observed especially at the lower layers. Innovative physical layer (PHY) concepts and technologies can be rapidly assimilated in cellular networks. Wireless mesh networks (WMNs), on the other hand, cannot keep up with the speed of innovation at the PHY due to their flat and decentralized architecture. Many innovative PHY technologies rely on multi-user communication, so that the established abstraction of the network stack does not work well for WMNs. The scheduling problem in WMNs is inherent complex. Surprisingly, carrier sense multiple access (CSMA) in WMNs is asymptotically utility-optimal even though it has a low computational complexity and does not involve message exchange. Hence, the question arises whether CSMA and the underlying concept of contention allows for the assimilation of advanced PHY technologies into WMNs. In this thesis, we design and evaluate contention protocols based on CSMA for opportunistic communication in WMNs. Opportunistic communication is a technique that relies on multi-user diversity in order to exploit the inherent characteristics of the wireless channel. In particular, we consider opportunistic routing (OR) and opportunistic scheduling (OS) in memoryless and slow fading channels, respectively. We present models for congestion control, routing and contention-based opportunistic communication in WMNs in order to maximize both throughput and fairness of elastic unicast traffic flows. At the instance of IEEE 802.11, we illustrate how the cross-layer algorithms can be implemented within a network simulator prototype. Our evaluation results lead to the conclusion that contention-based opportunistic communication is feasible. Furthermore, the proposed protocols increase both throughput and fairness in comparison to state-of-the-art approaches like DCF, DSR, ExOR, RBAR and ETT

Socio-economic aware data forwarding in mobile sensing networks and systems

The vision for smart sustainable cities is one whereby urban sensing is core to optimising city operation which in turn improves citizen contentment. Wireless Sensor Networks are envisioned to become pervasive form of data collection and analysis for smart cities but deployment of millions of inter-connected sensors in a city can be cost-prohibitive. Given the ubiquity and ever-increasing capabilities of sensor-rich mobile devices, Wireless Sensor Networks with Mobile Phones (WSN-MP) provide a highly flexible and ready-made wireless infrastructure for future smart cities. In a WSN-MP, mobile phones not only generate the sensing data but also relay the data using cellular communication or short range opportunistic communication. The largest challenge here is the efficient transmission of potentially huge volumes of sensor data over sometimes meagre or faulty communications networks in a cost-effective way. This thesis investigates distributed data forwarding schemes in three types of WSN-MP: WSN with mobile sinks (WSN-MS), WSN with mobile relays (WSN-HR) and Mobile Phone Sensing Systems (MPSS). For these dynamic WSN-MP, realistic models are established and distributed algorithms are developed for efficient network performance including data routing and forwarding, sensing rate control and and pricing. This thesis also considered realistic urban sensing issues such as economic incentivisation and demonstrates how social network and mobility awareness improves data transmission. Through simulations and real testbed experiments, it is shown that proposed algorithms perform better than state-of-the-art schemes.Open Acces

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

Towards video streaming in IoT environments: vehicular communication perspective

Multimedia oriented Internet of Things (IoT) enables pervasive and real-time communication of video, audio and image data among devices in an immediate surroundings. Today's vehicles have the capability of supporting real time multimedia acquisition. Vehicles with high illuminating infrared cameras and customized sensors can communicate with other on-road devices using dedicated short-range communication (DSRC) and 5G enabled communication technologies. Real time incidence of both urban and highway vehicular traffic environment can be captured and transmitted using vehicle-to-vehicle and vehicle-to-infrastructure communication modes. Video streaming in vehicular IoT (VSV-IoT) environments is in growing stage with several challenges that need to be addressed ranging from limited resources in IoT devices, intermittent connection in vehicular networks, heterogeneous devices, dynamism and scalability in video encoding, bandwidth underutilization in video delivery, and attaining application-precise quality of service in video streaming. In this context, this paper presents a comprehensive review on video streaming in IoT environments focusing on vehicular communication perspective. Specifically, significance of video streaming in vehicular IoT environments is highlighted focusing on integration of vehicular communication with 5G enabled IoT technologies, and smart city oriented application areas for VSV-IoT. A taxonomy is presented for the classification of related literature on video streaming in vehicular network environments. Following the taxonomy, critical review of literature is performed focusing on major functional model, strengths and weaknesses. Metrics for video streaming in vehicular IoT environments are derived and comparatively analyzed in terms of their usage and evaluation capabilities. Open research challenges in VSV-IoT are identified as future directions of research in the area. The survey would benefit both IoT and vehicle industry practitioners and researchers, in terms of augmenting understanding of vehicular video streaming and its IoT related trends and issues

Optimization and Learning in Energy Efficient Cognitive Radio System

Energy efficiency and spectrum efficiency are two biggest concerns for wireless communication. The constrained power supply is always a bottleneck to the modern mobility communication system. Meanwhile, spectrum resource is extremely limited but seriously underutilized. Cognitive radio (CR) as a promising approach could alleviate the spectrum underutilization and increase the quality of service. In contrast to traditional wireless communication systems, a distinguishing feature of cognitive radio systems is that the cognitive radios, which are typically equipped with powerful computation machinery, are capable of sensing the spectrum environment and making intelligent decisions. Moreover, the cognitive radio systems differ from traditional wireless systems that they can adapt their operating parameters, i.e. transmission power, channel, modulation according to the surrounding radio environment to explore the opportunity. In this dissertation, the study is focused on the optimization and learning of energy efficiency in the cognitive radio system, which can be considered to better utilize both the energy and spectrum resources. Firstly, drowsy transmission, which produces optimized idle period patterns and selects the best sleep mode for each idle period between two packet transmissions through joint power management and transmission power control/rate selection, is introduced to cognitive radio transmitter. Both the optimal solution by dynamic programming and flexible solution by reinforcement learning are provided. Secondly, when cognitive radio system is benefited from the theoretically infinite but unsteady harvested energy, an innovative and flexible control framework mainly based on model predictive control is designed. The solution to combat the problems, such as the inaccurate model and myopic control policy introduced by MPC, is given. Last, after study the optimization problem for point-to-point communication, multi-objective reinforcement learning is applied to the cognitive radio network, an adaptable routing algorithm is proposed and implemented. Epidemic propagation is studied to further understand the learning process in the cognitive radio network