1,272 research outputs found

    Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

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    Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

    Predictable Reliability In Inter-Vehicle Communications

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    Predictably reliable communication in wireless networked sensing and control systems (WSC) is a basic enabler for performance guarantee. Yet current research efforts are either focus on maximizing throughput or based on inaccurate interference modelling methods, which yield unsatisfactory results in terms of communication reliability. In this dissertation, we discuss techniques that enable reliable communication in both traditional wireless sensor networks and highly mobile inter-vehicle communication networks. We focus our discussion on traditional wireless sensor networks in Chapter 2 where we discuss mechanisms that enable predictable and reliable communications with no centralized infrastructures. With the promising results in Chapter 2, we extend our methods to inter-vehicle communication networks in Chapter 3. We focus on the broadcast communication paradigm and the unique challenges in applying the PRK interference model into broadcast problems in highly mobile inter-vehicle communication networks. While Chapter 2 and Chapter 3 focus on average reliability, we switch our problem to a more challenging aspect: guaranteeing short-term per-packet reception probability in Chapter 4. Specifically, we describe the PRKS protocol in Chapter 2 which considers unicast transmission paradigm in traditional static wireless sensor networks. PRKS uses the PRK interference model as a basis for interference relation identification that captures characteristics of wireless communications. For communication reliability control, we design a controller that runs at each link receiver and is able to control the average link reliability to be no lower than an application requirement as well as minimizing reliability variation. We further evaluate PRKS with extensive ns-3 simulations. The CPS protocol described in Chapter 3 considers an one-hop broadcast problem in multi-hop inter-vehicle communication networks. We analyze the challenges of applying the PRK model in this particular setting and propose an approximated PRK model, i.e., gPRK model, that addresses the challenges. We further design principles that CPS uses to instantiate the gPRK model in inter-vehicle communications. We implement the CPS scheduling framework in an integrated platform with SUMO and ns-3 to evaluate our design. In Chapter 4, we conservatively estimate the background interference plus noise while nodes are receiving packets. In the meantime, receivers decide minimum power levels their sender should use and feedback their decisions to their senders. Senders fuse feedbacks and choose a power level that guarantees expected packet reception probability at each receivers’ side. We notice in our evaluation that guaranteeing short-term reliability causes extra concurrency loss

    Predictable Reliability In Inter-Vehicle Communications

    Get PDF
    Predictably reliable communication in wireless networked sensing and control systems (WSC) is a basic enabler for performance guarantee. Yet current research efforts are either focus on maximizing throughput or based on inaccurate interference modelling methods, which yield unsatisfactory results in terms of communication reliability. In this dissertation, we discuss techniques that enable reliable communication in both traditional wireless sensor networks and highly mobile inter-vehicle communication networks. We focus our discussion on traditional wireless sensor networks in Chapter 2 where we discuss mechanisms that enable predictable and reliable communications with no centralized infrastructures. With the promising results in Chapter 2, we extend our methods to inter-vehicle communication networks in Chapter 3. We focus on the broadcast communication paradigm and the unique challenges in applying the PRK interference model into broadcast problems in highly mobile inter-vehicle communication networks. While Chapter 2 and Chapter 3 focus on average reliability, we switch our problem to a more challenging aspect: guaranteeing short-term per-packet reception probability in Chapter 4. Specifically, we describe the PRKS protocol in Chapter 2 which considers unicast transmission paradigm in traditional static wireless sensor networks. PRKS uses the PRK interference model as a basis for interference relation identification that captures characteristics of wireless communications. For communication reliability control, we design a controller that runs at each link receiver and is able to control the average link reliability to be no lower than an application requirement as well as minimizing reliability variation. We further evaluate PRKS with extensive ns-3 simulations. The CPS protocol described in Chapter 3 considers an one-hop broadcast problem in multi-hop inter-vehicle communication networks. We analyze the challenges of applying the PRK model in this particular setting and propose an approximated PRK model, i.e., gPRK model, that addresses the challenges. We further design principles that CPS uses to instantiate the gPRK model in inter-vehicle communications. We implement the CPS scheduling framework in an integrated platform with SUMO and ns-3 to evaluate our design. In Chapter 4, we conservatively estimate the background interference plus noise while nodes are receiving packets. In the meantime, receivers decide minimum power levels their sender should use and feedback their decisions to their senders. Senders fuse feedbacks and choose a power level that guarantees expected packet reception probability at each receivers’ side. We notice in our evaluation that guaranteeing short-term reliability causes extra concurrency loss

    Cross-layer latency-aware and -predictable data communication

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    Cyber-physical systems are making their way into more aspects of everyday life. These systems are increasingly distributed and hence require networked communication to coordinatively fulfil control tasks. Providing this in a robust and resilient manner demands for latency-awareness and -predictability at all layers of the communication and computation stack. This thesis addresses how these two latency-related properties can be implemented at the transport layer to serve control applications in ways that traditional approaches such as TCP or RTP cannot. Thereto, the Predictably Reliable Real-time Transport (PRRT) protocol is presented, including its unique features (e.g. partially reliable, ordered, in-time delivery, and latency-avoiding congestion control) and unconventional APIs. This protocol has been intensively evaluated using the X-Lap toolkit that has been specifically developed to support protocol designers in improving latency, timing, and energy characteristics of protocols in a cross-layer, intra-host fashion. PRRT effectively circumvents latency-inducing bufferbloat using X-Pace, an implementation of the cross-layer pacing approach presented in this thesis. This is shown using experimental evaluations on real Internet paths. Apart from PRRT, this thesis presents means to make TCP-based transport aware of individual link latencies and increases the predictability of the end-to-end delays using Transparent Transmission Segmentation.Cyber-physikalische Systeme werden immer relevanter für viele Aspekte des Alltages. Sie sind zunehmend verteilt und benötigen daher Netzwerktechnik zur koordinierten Erfüllung von Regelungsaufgaben. Um dies auf eine robuste und zuverlässige Art zu tun, ist Latenz-Bewusstsein und -Prädizierbarkeit auf allen Ebenen der Informations- und Kommunikationstechnik nötig. Diese Dissertation beschäftigt sich mit der Implementierung dieser zwei Latenz-Eigenschaften auf der Transport-Schicht, sodass Regelungsanwendungen deutlich besser unterstützt werden als es traditionelle Ansätze, wie TCP oder RTP, können. Hierzu wird das PRRT-Protokoll vorgestellt, inklusive seiner besonderen Eigenschaften (z.B. partiell zuverlässige, geordnete, rechtzeitige Auslieferung sowie Latenz-vermeidende Staukontrolle) und unkonventioneller API. Das Protokoll wird mit Hilfe von X-Lap evaluiert, welches speziell dafür entwickelt wurde Protokoll-Designer dabei zu unterstützen die Latenz-, Timing- und Energie-Eigenschaften von Protokollen zu verbessern. PRRT vermeidet Latenz-verursachenden Bufferbloat mit Hilfe von X-Pace, einer Cross-Layer Pacing Implementierung, die in dieser Arbeit präsentiert und mit Experimenten auf realen Internet-Pfaden evaluiert wird. Neben PRRT behandelt diese Arbeit transparente Übertragungssegmentierung, welche dazu dient dem TCP-basierten Transport individuelle Link-Latenzen bewusst zu machen und so die Vorhersagbarkeit der Ende-zu-Ende Latenz zu erhöhen
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