Design and implementation of a fault-tolerant multimedia network and a local map based (LMB) self-healing scheme for arbitrary topology networks.

by Arion Ko Kin Wa.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 101-[106]).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Overview --- p.1Chapter 1.2 --- Service Survivability Planning --- p.2Chapter 1.3 --- Categories of Outages --- p.3Chapter 1.4 --- Goals of Restoration --- p.4Chapter 1.5 --- Technology Impacts on Network Survivability --- p.5Chapter 1.6 --- Performance Models and Measures in Quantifying Network Sur- vivability --- p.6Chapter 1.7 --- Organization of Thesis --- p.6Chapter 2 --- Design and Implementation of A Survivable High-Speed Mul- timedia Network --- p.8Chapter 2.1 --- An Overview of CUM LAUDE NET --- p.8Chapter 2.2 --- The Network Architecture --- p.9Chapter 2.2.1 --- Architectural Overview --- p.9Chapter 2.2.2 --- Router-Node Design --- p.11Chapter 2.2.3 --- Buffer Allocation --- p.12Chapter 2.2.4 --- Buffer Transmission Priority --- p.14Chapter 2.2.5 --- Congestion Control --- p.15Chapter 2.3 --- Protocols --- p.16Chapter 2.3.1 --- Design Overview --- p.16Chapter 2.3.2 --- ACTA - The MAC Protocol --- p.17Chapter 2.3.3 --- Protocol Layering --- p.18Chapter 2.3.4 --- "Segment, Datagram and Packet Format" --- p.20Chapter 2.3.5 --- Fast Packet Routing --- p.22Chapter 2.3.6 --- Local Host NIU --- p.24Chapter 2.4 --- The Network Restoration Strategy --- p.25Chapter 2.4.1 --- The Dual-Ring Model and Assumptions --- p.26Chapter 2.4.2 --- Scenarios of Network Failure and Remedies --- p.26Chapter 2.4.3 --- Distributed Fault-Tolerant Algorithm --- p.26Chapter 2.4.4 --- Distributed Auto-Healing Algorithm --- p.28Chapter 2.4.5 --- The Network Management Signals --- p.31Chapter 2.5 --- Performance Evaluation --- p.32Chapter 2.5.1 --- Restoration Time --- p.32Chapter 2.5.2 --- Reliability Measures --- p.34Chapter 2.5.3 --- Network Availability During Restoration --- p.41Chapter 2.6 --- The Prototype --- p.42Chapter 2.7 --- Technical Problems Encountered --- p.45Chapter 2.8 --- Chapter Summary and Future Development --- p.46Chapter 3 --- A Simple Experimental Network Management Software - NET- MAN --- p.48Chapter 3.1 --- Introduction to NETMAN --- p.48Chapter 3.2 --- Network Management Basics --- p.49Chapter 3.2.1 --- The Level of Management Protocols --- p.49Chapter 3.2.2 --- Architecture Model --- p.51Chapter 3.2.3 --- TCP/IP Network Management Protocol Architecture --- p.53Chapter 3.2.4 --- A Standard Network Management Protocol On Internet - SNMP --- p.54Chapter 3.2.5 --- A Standard For Managed Information --- p.55Chapter 3.3 --- The CUM LAUDE Network Management Protocol Suite (CNMPS) --- p.56Chapter 3.3.1 --- The Architecture --- p.53Chapter 3.3.2 --- Goals of the CNMPS --- p.59Chapter 3.4 --- Highlights of NETMAN --- p.61Chapter 3.5 --- Functional Descriptions of NETMAN --- p.63Chapter 3.5.1 --- Topology Menu --- p.64Chapter 3.5.2 --- Fault Manager Menu --- p.65Chapter 3.5.3 --- Performance Meter Menu --- p.65Chapter 3.5.4 --- Gateway Utility Menu --- p.67Chapter 3.5.5 --- Tools Menu --- p.67Chapter 3.5.6 --- Help Menu --- p.68Chapter 3.6 --- Chapter Summary --- p.68Chapter 4 --- A Local Map Based (LMB) Self-Healing Scheme for Arbitrary Topology Networks --- p.70Chapter 4.1 --- Introduction --- p.79Chapter 4.2 --- An Overview of Existing DCS-Based Restoration Algorithms --- p.72Chapter 4.3 --- The Network Model and Assumptions --- p.74Chapter 4.4 --- Basics of the LMB Scheme --- p.75Chapter 4.4.1 --- Restoration Concepts --- p.75Chapter 4.4.2 --- Terminology --- p.76Chapter 4.4.3 --- Algorithm Parameters --- p.77Chapter 4.5 --- Performance Assessments --- p.78Chapter 4.6 --- The LMB Network Restoration Scheme --- p.80Chapter 4.6.1 --- Initialization - Local Map Building --- p.80Chapter 4.6.2 --- The LMB Restoration Messages Set --- p.81Chapter 4.6.3 --- Phase I - Local Map Update Phase --- p.81Chapter 4.6.4 --- Phase II - Update Acknowledgment Phase --- p.82Chapter 4.6.5 --- Phase III - Restoration and Confirmation Phase --- p.83Chapter 4.6.6 --- Phase IV - Cancellation Phase --- p.83Chapter 4.6.7 --- Re-Initialization --- p.84Chapter 4.6.8 --- Path Route Monitoring --- p.84Chapter 4.7 --- Performance Evaluation --- p.84Chapter 4.7.1 --- The Testbeds --- p.84Chapter 4.7.2 --- Simulation Results --- p.86Chapter 4.7.3 --- Storage Requirements --- p.89Chapter 4.8 --- The LMB Scheme on ATM and SONET environment --- p.92Chapter 4.9 --- Future Work --- p.94Chapter 4.10 --- Chapter Summary --- p.94Chapter 5 --- Conclusion and Future Work --- p.96Chapter 5.1 --- Conclusion --- p.95Chapter 5.2 --- Future Work --- p.99Bibliography --- p.101Chapter A --- Derivation of Communicative Probability --- p.107Chapter B --- List of Publications --- p.11

Distributed Failure Restoration for Asynchronous Transfer Mode (ATM) Tactical Communication Networks

Asynchronous Transfer Mode (A TM) is an attractive choice for future military communication systems because it can provide high throughput and support multi-service applications. Furthermore its use is consistent with the 'off the shelf technology policy that is currently operated by the Defence Engineering Research Agency of Great Britain. However, A TM has been developed as a civil standard and is designed to operate in network infrastructures with very low failure rates. In contrast, tactical networks are much less reliable. Indeed tactical networks operate on the premise that failures, particularly node failures, are expected. Hence, efficient, automatic failure restoration schemes are essential if an A TM based tactical network is to remain operational. The main objective of this research is the proposal and verification of one or more new restoration algorithms that meet the specific requirements of tactical networks. The aspects of ATM networks that influence restoration algorithms' implementation are discussed. In particular, the features of A TM networks such as the concept of Virtual Paths Virtual Channels and OAM (Operation And Maintenance) mechanisms that facilitate implementation of efficient restoration techniques. The unique characteristics of tactical networks and their impact on restoration are also presented. A significant part of the research was the study and evaluation of existing approaches to failure restoration in civil networks. A critical analysis of the suitability of these approaches to the tactical environment shows no one restoration algorithm fully meets the requirements of tactical networks. Consequently, two restoration algorithms for tactical A TM networks, DRA-TN (Dynamic Restoration Algorithm for Tactical Networks) and PPR-TN (Pre-planned Restoration Algorithm for Tactical Networks), are proposed and described in detail. Since the primary concern of restoration in tactical networks is the recovery of high priority connections the proposed algorithms attempt to restore high-priority connections by disrupting low-priority calls. Also, a number of additional mechanisms are proposed to reduce the use of bandwidth, which is a scarce resource in tactical networks. It is next argued that software simulation is the most appropriate method to prove the consistency of the proposed algorithms, assess their performance and test them on different network topologies as well as traffic and failure conditions. For this reason a simulation software package was designed and built specifically to model the proposed restoration algorithms. The design of the package is presented in detail and the most important implementation issues are discussed. The proposed restoration algorithms are modelled on three network topologies under various traffic loads, and their performance compared against the performance of known algorithms proposed for civil networks. It is shown that DRA-TN and PPR-TN provide better restoration of higher priority traffic. Furthermore, as the traffic load increases the relative performance of the DRA-TN and PPR-TN algorithms increases. The DRA-TN and PPR-TN algorithms are also compared and their advantages and disadvantages noted. Also, recommendations are given about the applicability of the proposed algorithms, and some practical implementation issues are discussed. The number of problems that need further study are briefly described.Defence Engineering Research Agency of Great Britai

An overview of memristive cryptography

Smaller, smarter and faster edge devices in the Internet of things era demands secure data analysis and transmission under resource constraints of hardware architecture. Lightweight cryptography on edge hardware is an emerging topic that is essential to ensure data security in near-sensor computing systems such as mobiles, drones, smart cameras, and wearables. In this article, the current state of memristive cryptography is placed in the context of lightweight hardware cryptography. The paper provides a brief overview of the traditional hardware lightweight cryptography and cryptanalysis approaches. The contrast for memristive cryptography with respect to traditional approaches is evident through this article, and need to develop a more concrete approach to developing memristive cryptanalysis to test memristive cryptographic approaches is highlighted.Comment: European Physical Journal: Special Topics, Special Issue on "Memristor-based systems: Nonlinearity, dynamics and applicatio

Methods of measuring residual stresses in components

Residual stresses occur in many manufactured structures and components. Large number of investigations have been carried out to study this phenomenon and its effect on the mechanical characteristics of these components. Over the years, different methods have been developed to measure residual stress for different types of components in order to obtain reliable assessment. The various specific methods have evolved over several decades and their practical applications have greatly benefited from the development of complementary technologies, notably in material cutting, full-field deformation measurement techniques, numerical methods and computing power. These complementary technologies have stimulated advances not only in measurement accuracy and reliability, but also in range of application; much greater detail in residual stresses measurement is now available. This paper aims to classify the different residual stresses measurement methods and to provide an overview of some of the recent advances in this area to help researchers on selecting their techniques among destructive, semi destructive and non destructive techniques depends on their application and the availabilities of those techniques. For each method scope, physical limitation, advantages and disadvantages are summarized. In the end this paper indicates some promising directions for future developments

A Unified Visual-Haptic Fingertip Sensor For Advanced Robot Dexterity

The problem of robotic grasping and manipulation requires a system level perspective that needs to be aimed at solving the interlinked sub-problems simultaneously. These sub-problems consists of designing an appropriate robot hand, sensing technology, control, and planning strategy, that can increase the dexterity of a robot hand in complex environments. Approaches towards these lack the proper use and integration of tactile feedback that can potentially enable robot hands with far superior capabilities than found today. This thesis addresses this challenge from three aspects: hardware design, system integration, and algorithm development. On the hardware side, it traces the thorough development of a multi and cross-modal tactile sensor that can measure proximity, contact, and force (PCF). Three unique features of the PCF sensor are (i) the ability to measure visual as well as tactile object features, (ii) its low manufacturing cost and (iii) that it can be easily integrated into different type of robot hands. This is achieved by embedding infrared proximity sensing integrated chips in soft elastomer to achieve a multitude of signals. On the system integration side, the thesis manifests the individual importance of the hand design, visual and tactile sensing modalities in the context of robotic manipulation related tasks through careful real-world robotic experiments. On the algorithmic side, it shows the implementation of several algorithms concerning signal processing, computer vision, controls, probabilistic theory and machine learning for experimental evaluation.</p

A Watershed Classification System Based on Headwater Catchments in Great Smoky Mountains National Park, Tennessee-North Carolina

Headwater areas in the southeastern U.S., as well as elsewhere, have received little attention from researchers, even though headwater catchments comprise over 70% of the land area in the southeastern highlands. The small, low-order streams that drain these catchments are greatly affected by hillslope processes within their watersheds. As such, there exists a strong link between upland landscape history and a headwater stream’s condition, including its channel morphology, habitat, and water quality. I employ this tight connection between landscape-scale attributes and reach-scale morphology in order to develop a headwater catchment classification system for Great Smoky Mountains National Park that describes the variation in stream channel morphology explicitly as a function of catchment characteristics. When developing a classification system, I test two separate classification techniques. First, I assess whether a ‘top-down’ statistical clustering approach, based exclusively on landscape-scale attributes, will distinguish groups of catchments that have significantly distinct types of stream channel morphology. In the second approach, the ‘bottom-up’ technique, I test whether catchments grouped by their respective distinct types of stream channels show any significant relationships between stream channel morphology and landscape-scale attributes. For the top-down technique, I use a geographic information system (GIS) and a digital elevation model (DEM) to delineate 862 headwater catchments in the study area; I then use a two-step clustering procedure to create six groups based on catchment area, circularity, resultant aspect, mean elevation, mean slope, and the percentages of burned area, pristine area, small-scale logging, extensive logging, settled areas, weak rocks, medium-strength rocks, strong rocks, and very strong rocks. Based on a stratified random sample, I use these groups to select 51 catchments for the collection of channel morphology information, which includes bankfull width, depth, and cross-sectional area, reach slope, median particle size, and the stored sediment in a riffle. These data are used to test the efficacy of the top-down technique in creating catchment groups with different types of stream channels based on an analysis of variance (ANOVA) procedure. For the bottom-up classification, I use the stream channel morphology data in a principal components analysis (PCA) and a two-step cluster procedure to create five groups of catchments based on the similarity of stream channel morphology information. I then use a multinomial logistic regression analysis to test how well the bottom-up classified catchment group membership is predicted when using the landscape-scale attributes as independent variables. Finally, I test if either headwater classification technique creates catchment groups with significantly different stream water chemistry. The top-down classification creates groups of catchments with different combinations of landscape-scale attributes, but these groups do not have significantly different types of stream channels. This is largely because the top-down approach is not a purely process-driven model; rather, it mathematically clusters groups according to a few dominant and shared landscape-scale attributes. As a result, some catchments have one or more statistically important but trivial attributes that offset the geomorphic influence of the dominant attribute on stream channel morphology. The top-down approach also does not account for convergence, where different combinations of attributes produce similar channel morphology. In contrast, the bottom-up approach is driven by geomorphic process; specifically, the catchment groups represent transitional states in the expected response to anthropogenic hillslope disturbances (logging intensity and settlement) of stream channels that are either aggrading, degrading, or in dynamic equilibrium. Bottom-up catchment group membership is predicted with better than 80% accuracy using the relationship between stream type and landscape-scale attributes. This occurs even though several bottom-up catchment groups share a few important landscape-scale attributes. Thus, various types of stream channels can form in similar catchments that differ only in disturbance intensity. Stream water chemistry does not differ between the top-down classified groups. However, with respect to the bottom-up classification, a significant difference exists between catchment groups regarding total nitrogen; catchment groups with high percentages of pristine forest have correspondingly high total nitrogen values as a result of nitrogen saturation in those areas. Landscape sensitivity, the degree of change in discharge and sediment flux following disturbance, is also possibly captured by the bottom-up watershed classification technique. As such, this more process-driven watershed classification serves as a metric in identifying the landscape-scale attributes that are most important in maintaining a particular type of stream channel morphology. Therefore, this classification allows researchers and land managers to anticipate possible changes in stream channel habitat as a function of proposed land use changes. It can also be used to identify areas that are particularly vulnerable to landscape change, as well as areas that might be somewhat resilient to various hillslope disturbance processes

3D Information Technologies in Cultural Heritage Preservation and Popularisation

This Special Issue of the journal Applied Sciences presents recent advances and developments in the use of digital 3D technologies to protect and preserve cultural heritage. While most of the articles focus on aspects of 3D scanning, modeling, and presenting in VR of cultural heritage objects from buildings to small artifacts and clothing, part of the issue is devoted to 3D sound utilization in the cultural heritage field