330 research outputs found

    Distributed filtering of networked dynamic systems with non-gaussian noises over sensor networks: A survey

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    summary:Sensor networks are regarded as a promising technology in the field of information perception and processing owing to the ease of deployment, cost-effectiveness, flexibility, as well as reliability. The information exchange among sensors inevitably suffers from various network-induced phenomena caused by the limited resource utilization and complex application scenarios, and thus is required to be governed by suitable resource-saving communication mechanisms. It is also noteworthy that noises in system dynamics and sensor measurements are ubiquitous and in general unknown but can be bounded, rather than follow specific Gaussian distributions as assumed in Kalman-type filtering. Particular attention of this paper is paid to a survey of recent advances in distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks. First, two types of widely employed structures of distributed filters are reviewed, the corresponding analysis is systematically addressed, and some interesting results are provided. The inherent purpose of adding consensus terms into the distributed filters is profoundly disclosed. Then, some representative models characterizing various network-induced phenomena are reviewed and their corresponding analytical strategies are exhibited in detail. Furthermore, recent results on distributed filtering with non-Gaussian noises are sorted out in accordance with different network-induced phenomena and system models. Another emphasis is laid on recent developments of distributed filtering with various communication scheduling, which are summarized based on the inherent characteristics of their dynamic behavior associated with mathematical models. Finally, the state-of-the-art of distributed filtering and challenging issues, ranging from scalability, security to applications, are raised to guide possible future research

    Distributed estimation techniques forcyber-physical systems

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    Nowadays, with the increasing use of wireless networks, embedded devices and agents with processing and sensing capabilities, the development of distributed estimation techniques has become vital to monitor important variables of the system that are not directly available. Numerous distributed estimation techniques have been proposed in the literature according to the model of the system, noises and disturbances. One of the main objectives of this thesis is to search all those works that deal with distributed estimation techniques applied to cyber-physical systems, system of systems and heterogeneous systems, through using systematic review methodology. Even though systematic reviews are not the common way to survey a topic in the control community, they provide a rigorous, robust and objective formula that should not be ignored. The presented systematic review incorporates and adapts the guidelines recommended in other disciplines to the field of automation and control and presents a brief description of the different phases that constitute a systematic review. Undertaking the systematic review many gaps were discovered: it deserves to be remarked that some estimators are not applied to cyber-physical systems, such as sliding mode observers or set-membership observers. Subsequently, one of these particular techniques was chosen, set-membership estimator, to develop new applications for cyber-physical systems. This introduces the other objectives of the thesis, i.e. to present two novel formulations of distributed set-membership estimators. Both estimators use a multi-hop decomposition, so the dynamics of the system is rewritten to present a cascaded implementation of the distributed set-membership observer, decoupling the influence of the non-observable modes to the observable ones. So each agent must find a different set for each sub-space, instead of a unique set for all the states. Two different approaches have been used to address the same problem, that is, to design a guaranteed distributed estimation method for linear full-coupled systems affected by bounded disturbances, to be implemented in a set of distributed agents that need to communicate and collaborate to achieve this goal

    A framework for the dynamic management of Peer-to-Peer overlays

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    Peer-to-Peer (P2P) applications have been associated with inefficient operation, interference with other network services and large operational costs for network providers. This thesis presents a framework which can help ISPs address these issues by means of intelligent management of peer behaviour. The proposed approach involves limited control of P2P overlays without interfering with the fundamental characteristics of peer autonomy and decentralised operation. At the core of the management framework lays the Active Virtual Peer (AVP). Essentially intelligent peers operated by the network providers, the AVPs interact with the overlay from within, minimising redundant or inefficient traffic, enhancing overlay stability and facilitating the efficient and balanced use of available peer and network resources. They offer an “insider‟s” view of the overlay and permit the management of P2P functions in a compatible and non-intrusive manner. AVPs can support multiple P2P protocols and coordinate to perform functions collectively. To account for the multi-faceted nature of P2P applications and allow the incorporation of modern techniques and protocols as they appear, the framework is based on a modular architecture. Core modules for overlay control and transit traffic minimisation are presented. Towards the latter, a number of suitable P2P content caching strategies are proposed. Using a purpose-built P2P network simulator and small-scale experiments, it is demonstrated that the introduction of AVPs inside the network can significantly reduce inter-AS traffic, minimise costly multi-hop flows, increase overlay stability and load-balancing and offer improved peer transfer performance

    Application and Theory of Multimedia Signal Processing Using Machine Learning or Advanced Methods

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    This Special Issue is a book composed by collecting documents published through peer review on the research of various advanced technologies related to applications and theories of signal processing for multimedia systems using ML or advanced methods. Multimedia signals include image, video, audio, character recognition and optimization of communication channels for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition. Academics and colleagues who are interested in these topics will find it interesting to read

    A Location Aware P2P Voice Communication Protocol for Networked Virtual Environments

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    Multiparty voice communication, where multiple people can communicate in a group, is an important component of networked virtual environments (NVEs), especially in many types of online games. While most research has been conducted on one-to-one communication, we focus on group communication. In this dissertation, we present the first measurement study on the characteristics of multiparty voice communications and develop a model of the talking and silence periods observed during multiparty communication. Over a total of 5 months, we measured over 11,000 sessions on an active multi-party voice communication server to quantify the characteristics of communication generated by game players, including group sizes, packet distributions, user and session frequencies, and speaking (and silence) durations. Further, we develop a model for multiparty voice communication that can be used for future research, simulation, network engineering, and game development work. Next, we propose a peer-to-peer protocol that uses Gabriel graphs, a subgraph of Delaunay-triangulations, to provide scalable multiparty voice communication. In addition, our protocol uses positional information so that voice data can be accurately modeled to listeners to increase the immersiveness of their experience. Our simulations show that the algorithms scale well even in densely populated areas, while prioritizing the sending of voice packets to the closest listeners of a speaker rst, thus behaving as users expect. We also develop a security framework that prevents common attacks. Finally, we implement our protocol and put it through exhaustive validation, where we use the model that we generated using our multiparty voice communication model

    Novel Transistor Resistance Variation-based Physical Unclonable Functions with On-Chip Voltage-to-Digital Converter Designed for Use in Cryptographic and Authentication Applications

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    Security mechanisms such as encryption, authentication, and feature activation depend on the integrity of embedded secret keys. Currently, this keying material is stored as digital bitstrings in non-volatile memory on FPGAs and ASICs. However, secrets stored this way are not secure against a determined adversary, who can use specialized probing attacks to uncover the secret. Furthermore, storing these pre-determined bitstrings suffers from the disadvantage of not being able to generate the key only when needed. Physical Unclonable Functions (PUFs) have emerged as a superior alternative to this. A PUF is an embedded Integrated Circuit (IC) structure that is designed to leverage random variations in physical parameters of on-chip components as the source of entropy for generating random and unique bitstrings. PUFs also incorporate an on-chip infrastructure for measuring and digitizing these variations in order to produce bitstrings. Additionally, PUFs are designed to reproduce a bitstring on-demand and therefore eliminate the need for on-chip storage. In this work, two novel PUFs are presented that leverage the random variations observed in the resistance of transistors. A thorough analysis of the randomness, uniqueness and stability characteristics of the bitstrings generated by these PUFs is presented. All results shown are based on an exhaustive testing of a set of 63 chips designed with numerous copies of the PUFs on each chip and fabricated in a 90nm nine-metal layer technology. An on-chip voltage-to-digital conversion technique is also presented and tested on the set of 63 chips. Statistical results of the bitstrings generated by the on-chip digitization technique are compared with that of the voltage-derived bitstrings to evaluate the efficacy of the digitization technique. One of the most important quality metrics of the PUF and the on-chip voltage-to-digital converter, the stability, is evaluated through a lengthy temperature-voltage testing over the range of -40C to +85C and voltage variations of +/- 10% of the nominal supply voltage. The stability of both the bitstrings and the underlying physical parameters is evaluated for the PUFs using the data collected from the hardware experiments and supported with software simulations conducted on the devices. Several novel techniques are proposed and successfully tested that address known issues related to instability of PUFs to changing temperature and voltage conditions, thus rendering our PUFs more resilient to these changing conditions faced in practical use. Lastly, an analysis of the stability to changing temperature and voltage variations of a third PUF that leverages random variations in the resistance of the metal wires in the power and ground grids of a chip is also presented
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