Delay control and parallel admission algorithms for real-time anycast flow

An anycast flow is a flow that can be connected to any one of the members in a group of designated (replicated) servers (called anycast group). In this paper, we derive a set of formulas for calculating the end-to-end delay bound for the anycast flows and present novel admission control algorithms for anycast flows with real-time constraints. Given such an anycast group, our algorithms can effectively select the paths for anycast flows' admission and connection based on the least end-to-end delay bounds evaluated. We also present a parallel admission control algorithm that can effectively calculate the available paths with a short delay bound for different destinations in the anycast group so that a best path with the shortest delay bound can be chosen.

Performance optimization for energy-aware adaptive checkpointing in embedded real-time systems

Using additional store-checkpoinsts (SCPs) and compare-checkpoints (CCPs), we present an adaptive checkpointing for double modular redundancy (DMR) in this paper. The proposed approach can dynamically adjust the checkpoint intervals. We also design methods to calculate the optimal numbers of checkpoints, which can minimize the average execution time of tasks. Further, the adaptive checkpointing is combined with the DVS (dynamic voltage scaling) scheme to achieve energy reduction. Simulation results show that, compared with the previous methods, the proposed approach significantly increases the likelihood of timely task completion and reduces energy consumption in the presence of faults.

Utility of real-time decision-making in commercial data stream mining domains

The objective is to measure utility of real-time commercial decision making. It is important due to a higher possibility of mistakes in real-time decisions, problems with recording actual occurrences, and significant costs associated with predictions produced by algorithms. The first contribution is to use overall utility and represent individual utility with a monetary value instead of a prediction. The second is to calculate the benefit from predictions using the utility-based decision threshold. The third is to incorporate cost of predictions. For experiments, overall utility is used to evaluate communal and spike detection, and their adaptive versions. The overall utility results show that with fewer alerts, communal detection is better than spike detection. With more alerts, adaptive communal and spike detection are better than their static versions. To maximise overall utility with all algorithms, only 1% to 4% in the highest predictions should be alerts.

Aura, real-time motion capture dance and 3D stereoscopic dance

Aura explored the potential of motion capture and 3D stereo projection to visualize 1950's dance philosopher, Susanne K. Langer's notion of 'virtual force'.

Key success factors in real-time industrial system assurance

The thesis analyses the issues of implementing real-time software systems in industrial applications. The benefit is the development of the Integrated Mega Project Development Model, to improve the effectiveness of planning and timely delivery of software, the quality of the delivered software and reducing problems associated with integrating software systems.

Prototyping real-time systems using Petri net and object-oriented models

The objective of the research for this thesis is to develop techniques in order to build an executable model of a real-time system. This model is to be used early in the development of the system not only to detect errors in the specification of the system but also to validate expectations of the developer as to the operation of the system. A graphical specification of a real-time system called the transformation schema was chosen to be used to build the model. Two executable models of a real-time system are described.

Kernel performance in meeting hard real-time system characteristics (the ARTOS real-time kernel)

Describes the design and implementation of an operating system kernel specifically designed to support real-time applications. It emphasises portability and aims to support state-of-the-art concepts in real-time programming. Discusses architectural aspects of the ARTOS kernel, and introduces new concepts on the areas of interrupt processing, scheduling, mutual exclusion and inter-task communication. Also explains the programming environment of ARTOS kernal and its task model, defines the real-time task states and system data structures and discusses exception handling mechanisms which are used to detect missed deadlines and take corrective action.

Time-of-flight secondary ion mass spectrometry investigation of epoxy resin curing behavior in real time

Time-of-flight secondary ion mass spectrometry and principal components analysis were used in real time to monitor the progress of curing reactions on the surface of a diglycidyl ether of bisphenol A (DGEBA) and diglycidyl ether of bisphenol F (DGEBF) epoxy resin blend reacted with the diamine hardener isophorone diamine at different time intervals. Molecular ions in the mass spectra that characterized the curing reactions steps, including blocking, coupling, branching, and crosslinking, were identified. The aliphatic hydrocarbon ions were correlated to the curing reaction rate, and this indicated that coupling and branching occurred much faster than the blocking and crosslinking curing reactions steps. The total conversion of the coupling and branching reaction steps were followed on the basis of changes with time in the relative ion intensity of molecular ions assigned to the DGEBA/DGEBF, aliphatic hydrocarbon, epoxide, and aromatic ring structures. Indicative measures of crosslinking density were monitored through the observation of changes in the ratio of the relative intensities of the aliphatic hydrocarbon and hydroxyl molecular ions over time. The curing reaction conversion was established by the observation of the changes in the relative ion intensity of the molecular ions that were related to the DGEBA/ DGEBF molecules.

Real-time early infectious outbreak detection systems using emerging technologies

The use of emerging technologies ( such as RFID - Radio Frequency Identification and remote sensing) can be employed to reduce health care costs and also to facilitate the automatic streamlining of infectious disease outbreak detection and monitoring processes in local health departments. It can assist medical practitioners with fast and accurate diagnosis and treatments. In this paper we outline the design and application of a real-time RFID and sensor-base Early Infectious (e.g., cholera) Outbreak Detection and Monitoring (IODM) system for health care.