73 research outputs found

    Improved Distributed Estimation Method for Environmental\ud time-variant Physical variables in Static Sensor Networks

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    In this paper, an improved distributed estimation scheme for static sensor networks is developed. The scheme is developed for environmental time-variant physical variables. The main contribution of this work is that the algorithm in [1]-[3] has been extended, and a filter has been designed with weights, such that the variance of the estimation errors is minimized, thereby improving the filter design considerably\ud and characterizing the performance limit of the filter, and thereby tracking a time-varying signal. Moreover, certain parameter optimization is alleviated with the application of a particular finite impulse response (FIR) filter. Simulation results are showing the effectiveness of the developed estimation algorithm

    An SDN-based firewall shunt for data-intensive science applications

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    A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2016Data-intensive research computing requires the capability to transfer les over long distances at high throughput. Stateful rewalls introduce su cient packet loss to prevent researchers from fully exploiting high bandwidth-delay network links [25]. To work around this challenge, the science DMZ design [19] trades o stateful packet ltering capability for loss-free forwarding via an ordinary Ethernet switch. We propose a novel extension to the science DMZ design, which uses an SDN-based rewall. This report introduces NFShunt, a rewall based on Linux's Net lter combined with OpenFlow switching. Implemented as an OpenFlow 1.0 controller coupled to Net lter's connection tracking, NFShunt allows the bypass-switching policy to be expressed as part of an iptables rewall rule-set. Our implementation is described in detail, and latency of the control-plane mechanism is reported. TCP throughput and packet loss is shown at various round-trip latencies, with comparisons to pure switching, as well as to a high-end Cisco rewall. Cost, as well as operations and maintenance aspects, are compared and analysed. The results support reported observations regarding rewall introduced packet-loss, and indicate that the SDN design of NFShunt is a technically viable and cost-e ective approach to enhancing a traditional rewall to meet the performance needs of data-intensive researchersGS201

    Event-Triggered Consensus and Formation Control in Multi-Agent Coordination

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    The focus of this thesis is to study distributed event-triggered control for multi-agent systems (MASs) facing constraints in practical applications. We consider several problems in the field, ranging from event-triggered consensus with information quantization, event-triggered edge agreement under synchronized/unsynchronized clocks, event-triggered leader-follower consensus with Euler-Lagrange agent dynamics and cooperative event-triggered rigid formation control. The first topic is named as event-triggered consensus with quantized relative state measurements. In this topic, we develop two event-triggered controllers with quantized relative state measurements to achieve consensus for an undirected network where each agent is modelled by single integrator dynamics. Both uniform and logarithmic quantizers are considered, which, together with two different controllers, yield four cases of study in this topic. The quantized information is used to update the control input as well as to determine the next trigger event. We show that approximate consensus can be achieved by the proposed algorithms and Zeno behaviour can be completely excluded if constant offsets with some computable lower bounds are added to the trigger conditions. The second topic considers event-triggered edge agreement problems. Two cases, namely the synchronized clock case and the unsynchronized clock case, are studied. In the synchronized clock case, all agents are activated simultaneously to measure the relative state information over edge links under a global clock. Edge events are defined and their occurrences trigger the update of control inputs for the two agents sharing the link. We show that average consensus can be achieved with our proposed algorithm. In the unsynchronized clock case, each agent executes control algorithms under its own clock which is not synchronized with other agents' clocks. An edge event only triggers control input update for an individual agent. It is shown that all agents will reach consensus in a totally asynchronous manner. In the third topic, we propose three different distributed event-triggered control algorithms to achieve leader-follower consensus for a network of Euler-Lagrange agents. We firstly propose two model-independent algorithms for a subclass of Euler-Lagrange agents without the vector of gravitational potential forces. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work concerning event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information and bounds on the initial conditions. When the Euler-Lagrange agents have dynamics which include the vector of gravitational potential forces, an adaptive algorithm is proposed. This requires more information about the agent dynamics but allows for the estimation of uncertain agent parameters. The last topic discusses cooperative stabilization control of rigid formations via an event-triggered approach. We first design a centralized event-triggered formation control system, in which a central event controller determines the next triggering time and broadcasts the event signal to all the agents for control input update. We then build on this approach to propose a distributed event control strategy, in which each agent can use its local event trigger and local information to update the control input at its own event time. For both cases, the trigger condition, event function and trigger behaviour are discussed in detail, and the exponential convergence of the formation system is guaranteed

    Authentication enhancement in command and control networks: (a study in Vehicular Ad-Hoc Networks)

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    Intelligent transportation systems contribute to improved traffic safety by facilitating real time communication between vehicles. By using wireless channels for communication, vehicular networks are susceptible to a wide range of attacks, such as impersonation, modification, and replay. In this context, securing data exchange between intercommunicating terminals, e.g., vehicle-to-everything (V2X) communication, constitutes a technological challenge that needs to be addressed. Hence, message authentication is crucial to safeguard vehicular ad-hoc networks (VANETs) from malicious attacks. The current state-of-the-art for authentication in VANETs relies on conventional cryptographic primitives, introducing significant computation and communication overheads. In this challenging scenario, physical (PHY)-layer authentication has gained popularity, which involves leveraging the inherent characteristics of wireless channels and the hardware imperfections to discriminate between wireless devices. However, PHY-layerbased authentication cannot be an alternative to crypto-based methods as the initial legitimacy detection must be conducted using cryptographic methods to extract the communicating terminal secret features. Nevertheless, it can be a promising complementary solution for the reauthentication problem in VANETs, introducing what is known as “cross-layer authentication.” This thesis focuses on designing efficient cross-layer authentication schemes for VANETs, reducing the communication and computation overheads associated with transmitting and verifying a crypto-based signature for each transmission. The following provides an overview of the proposed methodologies employed in various contributions presented in this thesis. 1. The first cross-layer authentication scheme: A four-step process represents this approach: initial crypto-based authentication, shared key extraction, re-authentication via a PHY challenge-response algorithm, and adaptive adjustments based on channel conditions. Simulation results validate its efficacy, especially in low signal-to-noise ratio (SNR) scenarios while proving its resilience against active and passive attacks. 2. The second cross-layer authentication scheme: Leveraging the spatially and temporally correlated wireless channel features, this scheme extracts high entropy shared keys that can be used to create dynamic PHY-layer signatures for authentication. A 3-Dimensional (3D) scattering Doppler emulator is designed to investigate the scheme’s performance at different speeds of a moving vehicle and SNRs. Theoretical and hardware implementation analyses prove the scheme’s capability to support high detection probability for an acceptable false alarm value ≀ 0.1 at SNR ≄ 0 dB and speed ≀ 45 m/s. 3. The third proposal: Reconfigurable intelligent surfaces (RIS) integration for improved authentication: Focusing on enhancing PHY-layer re-authentication, this proposal explores integrating RIS technology to improve SNR directed at designated vehicles. Theoretical analysis and practical implementation of the proposed scheme are conducted using a 1-bit RIS, consisting of 64 × 64 reflective units. Experimental results show a significant improvement in the Pd, increasing from 0.82 to 0.96 at SNR = − 6 dB for multicarrier communications. 4. The fourth proposal: RIS-enhanced vehicular communication security: Tailored for challenging SNR in non-line-of-sight (NLoS) scenarios, this proposal optimises key extraction and defends against denial-of-service (DoS) attacks through selective signal strengthening. Hardware implementation studies prove its effectiveness, showcasing improved key extraction performance and resilience against potential threats. 5. The fifth cross-layer authentication scheme: Integrating PKI-based initial legitimacy detection and blockchain-based reconciliation techniques, this scheme ensures secure data exchange. Rigorous security analyses and performance evaluations using network simulators and computation metrics showcase its effectiveness, ensuring its resistance against common attacks and time efficiency in message verification. 6. The final proposal: Group key distribution: Employing smart contract-based blockchain technology alongside PKI-based authentication, this proposal distributes group session keys securely. Its lightweight symmetric key cryptography-based method maintains privacy in VANETs, validated via Ethereum’s main network (MainNet) and comprehensive computation and communication evaluations. The analysis shows that the proposed methods yield a noteworthy reduction, approximately ranging from 70% to 99%, in both computation and communication overheads, as compared to the conventional approaches. This reduction pertains to the verification and transmission of 1000 messages in total

    Telecommunication Systems

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    This book is based on both industrial and academic research efforts in which a number of recent advancements and rare insights into telecommunication systems are well presented. The volume is organized into four parts: "Telecommunication Protocol, Optimization, and Security Frameworks", "Next-Generation Optical Access Technologies", "Convergence of Wireless-Optical Networks" and "Advanced Relay and Antenna Systems for Smart Networks." Chapters within these parts are self-contained and cross-referenced to facilitate further study

    Networks of Liveness in Singer-Songwriting: A practice-based enquiry into developing audio-visual interactive systems and creative strategies for composition and performance.

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    This enquiry explores the creation and use of computer-based, real-time interactive audio-visual systems for the composition and performance of popular music by solo artists. Using a practice-based methodology, research questions are identified that relate to the impact of incorporating interactive systems into the songwriting process and the liveness of the performances with them. Four approaches to the creation of interactive systems are identified: creating explorative-generative tools, multiple tools for guitar/vocal pieces, typing systems and audio-visual metaphors. A portfolio of ten pieces that use these approaches was developed for live performance. A model of the songwriting process is presented that incorporates system-building and strategies are identified for reconciling the indeterminate, electronic audio output of the system with composed popular music features and instrumental/vocal output. The four system approaches and ten pieces are compared in terms of four aspects of liveness, derived from current theories. It was found that, in terms of overall liveness, a unity to system design facilitated both technological and aesthetic connections between the composition, the system processes and the audio and visual outputs. However, there was considerable variation between the four system approaches in terms of the different aspects of liveness. The enquiry concludes by identifying strategies for maximising liveness in the different system approaches and discussing the connections between liveness and the songwriting process

    Hierarchical clustering-based segmentation (HCS) aided diagstic image interpretation monitoring.

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    Machines are good at operations which require precision and computing objective measures. In contrast, humans are good at generalisation and making decisions based on their past experience and heuristics. Hence, to solve any problem with a solution involving human-machine interaction, it is imperative that the tasks are shared appropriately. However, the boundary which divides these two different set of tasks is not well defined in domains such as medical image interpretation. Therefore, one needs a versatile tool which is flexible enough to accommodate the varied requirements of the user. The aim of this study is to design and implement such a software tool to aid the radiologists in the interpretation of diagnostic images.Tissue abnormality in a medical image is usually related to a dissimilar part of an otherwise homogeneous image. The dissimilarity may be subtle or strong depending on the medical modality and the type of abnormal tissue. Hierarchical Clustering-based Segmentation (HCS) process is a dissimilarity highlighting process that yields a hierarchy of segmentation results. In this study, the HCS process was investigated for offering the user a versatile and flexible environment to perceive the varied dissimilarities that might be present in diagnostic images. Consequently, the user derives the maximum benefit from the computational capability (perception) of the machine and at the same time incorporate their own decision process (interpretation) at the appropriate places.As a result of the above investigation, this study demonstrates how HCS process can be used to aid radiologists in their interpretive tasks. Specifically this study has designed the following HCS process aided diagnostic image interpretation applications: interpretation of computed tomography (CT) images of the lungs to quantitatively measure the dimensions of the airways and the accompanying blood vessels; Interpretation of X-ray mammograms to quantitatively differentiate benign from malignant abnormalities. One of the major contribution of this study is to demonstrate how the above HCS process aided interpretation of diagnostic images can be used to monitor disease conditions. This thesis details the development and evaluation of the novel computer aided monitoring (CAM) system. The designed CAM system is used to objectively measure the properties of suspected abnormal areas in the CT images of the lungs and in X-ray mammogram. Thus, the CAM system can be used to assist the clinician to objectively monitor the abnormality. For instance, its response to treatment and consequently its prognosis. The implemented CAM system to monitor abnormalities in X-ray mammograms is briefly described below. Using the approximate location and size of the abnormality, obtained from the user, the HCS process automatically identifies the more appropriate boundaries of the different regions within a region of interest (ROI), centred at the approximate location. From the set of, HCS process segmented, regions the user identifies the regions which most likely represent the abnormality and the healthy areas. Subsequently, the CAM system compares the characteristics of the user identified abnormal region with that of the healthy region; to differentiate malignant from benign abnormality. In processing sixteen mammograms, the designed CAM system demonstrated the possibility of successfully differentiating malignant from benign abnormalities

    Research report .... 2010–2012

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    Computation offloading for algorithms in absence of the Cloud

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    Mobile cloud computing is a way of delegating complex algorithms from a mobile device to the cloud to complete the tasks quickly and save energy on the mobile device. However, the cloud may not be available or suitable for helping all the time. For example, in a battlefield scenario, the cloud may not be reachable. This work considers neighbouring devices as alternatives to the cloud for offloading computation and presents three key contributions, namely a comprehensive investigation of the trade-off between computation and communication, Multi-Objective Optimisation based approach to offloading, and Queuing Theory based algorithms that present the benefits of offloading to neighbours. Initially, the states of neighbouring devices are considered to be known and the decision of computation offloading is proposed as a multi-objective optimisation problem. Novel Pareto optimal solutions are proposed. The results on a simulated dataset show up to 30% increment in performance even when cloud computing is not available. However, information about the environment is seldom known completely. In Chapter 5, a realistic environment is considered such as delayed node state information and partially connected sensors. The network of sensors is modelled as a network of queues (Open Jackson network). The offloading problem is posed as minimum cost problem and solved using Linear solvers. In addition to the simulated dataset, the proposed solution is tested on a real computer vision dataset. The experiments on the random waypoint dataset showed up to 33% boost on performance whereas in the real dataset, exploiting the temporal and spatial distribution of the targets, a significantly higher increment in performance is achieved

    Pacific Symposium on Biocomputing 2023

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    The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field
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