Browsing by Subject "Real-time data processing"
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Item Analog VLSI implementation of a Gabor convolution for real time image processing(Texas Tech University, 1996-05) Moldovan, LaszloNot availableItem Design of a real-time control systems laboratory(Texas Tech University, 1986-05) Matos, Mark LuisNot availableItem Design of real-time virtual resource architecture for large-scale embedded systems(2004) Feng, Xiang; Mok, Aloysius Ka-Lau.Embedded computers have become pervasive and complex. Every microwave oven has one. The Volvo S80 has more than fifty. A Boeing 777-300 has hundreds. Meanwhile, more and more embedded systems are inter-connected to perform so- phisticated functions on their hosts such as the air information management sys- tems on modern aircrafts. However, due to real-time and fault-tolerance concerns, embedded systems are traditionally implemented on dedicated hardware. This ap- proach entails at least three serious consequences: firstly, profligate and rigid usage of resources necessitated by the binding of subsystems to hardware platforms; sec- ondly, significantly more difficult system integration because individually developed and tested systems are not guaranteed to work in combination; thirdly, the lack of higher-level system control because conceptually indivisible functions are isolated on the hardware level. These problems have caused not only financial loss such as unusable systems due to the high cost of unjustified resource redundancy and integration failures, but also the loss of human lives as exemplified by a number of fatal accidents induced by the third problem. It is critical that system engineers have a solid basis for addressing these fundamental design problems in large-scale real-time embedded systems. An ideal solution should achieve a complete separa- tion of concerns so that: (1) each task group may be executed as if it had access to its own dedicated resource, (2) there is minimal interaction between the resource level scheduler and the task level scheduler, and (3) in case of hardware failure, task groups could easily migrate to other resources. Towards this end, in this dissertation we introduce the notion of a Real-Time Virtual Resource (RTVR) which operates at a fraction of the rate of the shared physical resource and whose rate of operation varies with time but is bounded. Tasks within the same task group are scheduled by a task level scheduler that is specialized to the real-time requirements of the tasks in the group. The scheduling problems on both task level and resource level are analyzed. We specifically investigate RTVRs on the integer domain. For the case of regular resource partitioning, we show that the utilization bounds of both fixed- priority scheduling and dynamic-priority scheduling remain unchanged from those for dedicated resources. We determine the utilization bounds for the more general case of irregular partitioning. In particular, both types of partitions can be effi- ciently constructed by exploiting compositionality properties vis-a-vis the regularity measure. We further extend the applicability of the RTVR in several directions. First, we propose a hierarchical real-time virtual resource model that permits resource partitioning to be extended to multiple levels. Through this model, partitions on each level are scheduled as if they had access to a dedicated resource. Interference between neighboring partition levels is also minimized. Second, we apply RTVR to gang scheduling which is a popular scheduling technique used in parallel systems. We show that the clean isolation between resource-level and task-level scheduling makes RTVR an ideal candidate for implementing the gang scheduling solution in the real-time systems environment. Third, RTVRs in distributed environments are also discussed and end-to-end delay of a series of RTVRs is calculated. Finally, we investigate the resource locking issues in RTVR and present a resource server solution which has a highly efficient admission test. We also present an optimization scheme called Partition Coalition which is based on the server solution and which can substantially reduce the blocking time due to resource locking. These results provide a foundation for implementing RTVR on small-scale multiprocessor or processor cluster systems that are increasingly available. Based on the previous theoretical framework, we implement RTVRs on the Linux 2.4 kernel. The first RTVR implementation uses a static resource level sched- uler which can be applied to systems with predefined application task sets. The second implementation has a novel dynamic resource level scheduler under which task groups can join and leave dynamically. We further virtualize network devices. Several experiments are conducted to measure system performance in various as- pects such as the effect of the scheduling quantum size, interrupt request response time and scheduling overhead. The experiments demonstrate that RTVRs can be efficiently implemented while satisfying their theoretical properties.Item Design of software for real-time multitasking control system(Texas Tech University, 1988-05) Chang, Hua Wu DavidThe trend in real-time control systems is toward using larger and more sophisticate software. The use of a realtime, multitasking operating system for providing an environment under which multiple tasks can be executed concurrently is considerable a good approach for developing the real-time control software. However, developing a successful real-time, multitasking control software is not easy. Several critical factors might be potential bottlenecks in the system. These factors are task definition, task control flow design, intertask communication, real-time response, interfaces with the outside world, mutual exclusion, and evaluation of performance. The objective of this thesis is to explore the implementation details of a real-time, multitasking control system (RMCS) and to provide insights and methods for mitigating problems contained in these factors. The insights and methods developed are illustrated through references to a successful implementation of a real-time, multitasking control system for semiconductor processing equipment.Item Inference of task execution times using linear regression techniques(Texas Tech University, 2002-12) Muniyappa, VinayNot availableItem Integration of hard real-time schedulers(2004) Wang, Weirong; Mok, Aloysius Ka-Lau.Item Joint source-channel distortion modeling for image and video communication(2006) Sabir, Muhammad Farooq; Bovik, Alan C. (Alan Conrad), 1958-; Heath, Robert W., Ph. D.Item Item Peak-To-Average Ration Reduction Algorithms For Multicarrier Modulation Systems(Texas Tech University, 2002-05) Singleton, Victor CodyMulticarrier modulation (MCM) systems signals have found increasing use in modern communication systems, including both wireline and wireless environments. However, MCM signals have the potential to contain large instantaneous peaks that increase the resolution requirements of the A/D-D/A converters as well as the dynamic range requirements of the transmitter. By limiting the maximum amplitude of the MCM signal (clipping), it is possible to reduce these requirements on the transmitter's analog front-end circuitry. However, if the transmitter clips the MCM signal, information is lost and the receiver may not be able to properly demodulate the signal. Applying a peak-to-average ratio (PAR) reduction algorithm at the transmitter can mitigate the adverse effects of clipping a MCM signal. The performance and implementation complexity of existing PAR reduction algorithms in addition to a novel PAR reduction algorithm were evaluated via simulation, and these results will be discussed and contrasted. PAR reduction methods that require no additional processing at the receiver were evaluated as well as methods that require receiver intervention.Item Real time digital signal processing(Texas Tech University, 1982-05) Londono, Luis EduardoNot availableItem Real-time automated data acquisition and control for the Crosbyton Solar Power Project(Texas Tech University, 1980-12) Edwards, William HNot availableItem Real-time scheduling with soft deadlines and cost/value functions(Texas Tech University, 1995-12) Durai, ParthibanThe use of a central facility for performing modeling and optimization operations is an approach employed in improving overall performance in manufacturing environments. Such a facility may be thought of to operate using the well established client-server architecmre, wherein the facility performs the role of the server. The prototype system built using die Simplex architecmre [2], defmed by the Software Engineering Institute (SEI) at Carnegie MeUon University and the Hybrid Modellng Facility [3], may be considered to fall under this category. Faculties such as those mentioned above are essentially real-time systems and are used largely in a manufacturing oriented shop floor environment. Such systems usually behave more as soft real-time systems rather than hard ones. The reason for this, is that, the failure to meet deadlines of tasks in the system may not lead to catastrophic failure. The scheduler forms an integral part of such systems and essentially decides on the execution ordering of the tasks, corresponding to the requests received. This ordering is dependent, in turn, on the algorithm that is used. The aim of this study is to improve the operation of a simulated system based on the above mentioned architectures, by providing appropriate scheduling algorithms for the ordering of tasks that are to be executed, in response to requests from clients. By appropriate we mean that the scheduling algorithm will take into account the fact that tasks in the system operate under soft deadlines rather that hard ones, and also incorporate the cost or value factors that may be associated with the requests.Item Space-variant optical processing with acousto-optic modulators(Texas Tech University, 1984-12) Lojewski, David Y.Chapter 2 presents the theoretical background of the two major parts of the experiment: space-variant processing and acousto-optic modulators. These two areas form the basis for understanding the experiment. Chapter 3 describes the proof-of-principle experiment that was designed. The equipment used is identified and the development of the computer control is presented. The results are given and a comparison is made between the calculated and the measured results. Chapter 4 goes into the capabilities of the experiment. The physical limitations of the equipment is discussed and some indication of the potential for this design is given. Chapter 5 sums up the experiment and discusses possible areas for future research.Item Time series prediction using real-time recurrent networks(Texas Tech University, 1997-05) Li, RuinaThe purpose of this work is to investigate the possibility of using time series prediction of the Electrocardiogram (ECG) data by the Real-Time Recurrent Networks (RTRN). The RTRN models have been constructed using the Real-Time Recurrent Learning (RTRL) algorithm with teacher forcing. Both single-point prediction and multi-point prediction were used to forecast the ECG behaviors. The ECG data come from the ECG recordings gathered from a group of patients by the Massachusetts Institute of Technology Division of Health Sciences and Technology. The RTRNs were trained with normal ECG data and were used to predict both normal and abnormal ECG behaviors of the same patient. We found that the single-point prediction of most RTRNs achieved successful results in the forecasting of both normal and abnormal ECG behaviors. However, the multi-point prediction fails to produce the desired results.