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A Survey of Algorithms for RealTime Bayesian Network Inference
 In In the joint AAAI02/KDD02/UAI02 workshop on RealTime Decision Support and Diagnosis Systems
, 2002
"... As Bayesian networks are applied to more complex and realistic realworld applications, the development of more efficient inference algorithms working under realtime constraints is becoming more and more important. This paper presents a survey of various exact and approximate Bayesian network ..."
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Cited by 46 (2 self)
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As Bayesian networks are applied to more complex and realistic realworld applications, the development of more efficient inference algorithms working under realtime constraints is becoming more and more important. This paper presents a survey of various exact and approximate Bayesian network inference algorithms. In particular, previous research on realtime inference is reviewed. It provides a framework for understanding these algorithms and the relationships between them. Some important issues in realtime Bayesian networks inference are also discussed.
Scheduling Hard RealTime Tasks with Tolerance of Multiple Processor Failures
 MULTIPROCESSING AND MULTIPROGRAMMING
, 1993
"... Realtime systems are being extensively used in applications that are ..."
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Cited by 13 (2 self)
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Realtime systems are being extensively used in applications that are
The Design and Analysis of Scheduling Algorithms for RealTime and FaultTolerant Computer Systems
, 1994
"... ..."
Performance evaluation of scheduling algorithms for imprecise computer systems
 Journal of Systems and Software
, 1991
"... We study the scheduling of tasks in computer systems which utilize imprecise (partial) computations. In our system, tasks arrive randomly during runtime. Each task has two levels of computation time requirements: the full level computation requirement and the reduced level computation requirement. ..."
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Cited by 9 (0 self)
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We study the scheduling of tasks in computer systems which utilize imprecise (partial) computations. In our system, tasks arrive randomly during runtime. Each task has two levels of computation time requirements: the full level computation requirement and the reduced level computation requirement. The reduced level computation of a task takes less time to accomplish than the full level, but produces results which are not as precise as those of fulllevel computation. We assume that the imprecise results are nonetheless acceptable. The tasks are scheduled in the following way: If the total number of tasks in the system is no more than Ma system parameterthe tasks are executed at the full level. When the total number of tasks exceeds M, the tasks are executed at the reduced level. The system performance under this kind of scheduling and computation model is analyzed. Attention is devoted to development of the explicit formulas for the practically important performance metrics such as the normalized mean task waiting time, the mean task served computation time, and the fraction of tasks fully processed. The effect of variations in parameter values on the system performance is also examined in detail. 1.
The Theory of Task Scheduling in RealTime Systems: Compilation and Systematization of the Main Results
, 1999
"... to the early years of 1973, there has a signi cant increase in awareness both in industry and in academia, of the importance of task scheduling in realtime systems because of the varied elds of applications and some important results recently published. Every realtime system designer should be f ..."
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Cited by 2 (0 self)
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to the early years of 1973, there has a signi cant increase in awareness both in industry and in academia, of the importance of task scheduling in realtime systems because of the varied elds of applications and some important results recently published. Every realtime system designer should be familiar with a set of important scheduling theory results, because analysis of xed priority scheduling has now progressed to the point where it provides an appropriate framework for the construction of many of today's hard realtime systems. The idea to produce this thesis goes back to the article Dise~no de Sistemas de Tiempo Real of Guillem Bernat, Albert Llamos and Ramon Puigjaner, that was published in Novatica in 1997 [BLP97]. Motivated by the lack of literature that both proportiones and systematizes the results of xed priority preemptive scheduling of realtime systems we now present the most relevant work done on this eld of research in a new way: The Theory of Task Scheduling
Scheduling Hard RealTime Tasks with 1ProcessorFaultTolerance
 MULTIPROCESSING AND MULTIPROGRAMMING
, 1993
"... Realtime systems are being extensively used in applications that are missioncritical and lifecritical, such as space exploration, aircraft avionics, and robotics. Since these systems are usually operating in environments that are nondeterministic, and even hazardous, it is extremely important th ..."
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Cited by 2 (0 self)
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Realtime systems are being extensively used in applications that are missioncritical and lifecritical, such as space exploration, aircraft avionics, and robotics. Since these systems are usually operating in environments that are nondeterministic, and even hazardous, it is extremely important that hard deadlines of tasks be met even in the presence of certain failures. To tolerate processor failures in a realtime multiprocessor system, the problem of scheduling a set of hard realtime tasks with duplication is studied. We first prove that the problem of scheduling a set of nonpreemptive tasks on m ³ 3 processors to tolerate one arbitrary processor failure is NPcomplete even when the tasks share a common deadline. A heuristic algorithm is then proposed to solve the problem. The schedule generated by the scheduling algorithm can tolerate, in the worst case, one arbitrary processor failure, but in the best case processor failures, where m is the number of processors in the system. ...
Preemptive Scheduling of Tasks with Reliability Requirements in Distributed Hard RealTime Systems
, 1993
"... Realtime systems are being extensively used in applications that are missioncritical and lifecritical, such as space exploration, aircraft avionics, and robotics. These mission critical systems are mainly parallel or distributed systems that are embedded into complex, even hazardous environments, ..."
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Realtime systems are being extensively used in applications that are missioncritical and lifecritical, such as space exploration, aircraft avionics, and robotics. These mission critical systems are mainly parallel or distributed systems that are embedded into complex, even hazardous environments, under tight constraints on timeliness and dependability of operations. It is therefore extremely important that these hard realtime systems must be reliable, i.e., task deadlines be met even in the presence of certain faults or failures. In this paper, we address the problem of supporting timeliness and dependability in a realtime system at the level of task scheduling. We consider the problem of scheduling a set of tasks, each of which, for faulttolerance purpose, has multiple versions, on a number of processors, such that the number of processors used is minimized. Two scheduling algorithms are proposed and evaluated using simulation. It is shown that the algorithms produce nearoptima...
by
, 2008
"... This thesis is concerned with the design and implementation of singleprocessor embedded realtime systems with highly predictable behaviour and strict constraints on resource usage. The main aim of this research is to identify the sources of unpredictable behaviour in such systems – exhibited as ti ..."
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This thesis is concerned with the design and implementation of singleprocessor embedded realtime systems with highly predictable behaviour and strict constraints on resource usage. The main aim of this research is to identify the sources of unpredictable behaviour in such systems – exhibited as timing jitter when a timetriggered preemptive task scheduling approach is adopted, and then provide software based techniques to enhance their temporal predictability. The thesis provides a review of related previous work on predictable realtime task scheduling, as well as resourceaccess control methods for maintaining predictable realtime system behaviour through the prevention of priority inversion and other related problems. The design and implementation of the timetriggered hybrid (TTH), timetriggered ratemonotonic (TTRM), and timetriggered deadlinemonotonic (TTDM) task schedulers is discussed in detail as they provide the most predictable behaviour within the category of preemptive task schedulers. For that reason, they will be used
The Tyche CPU Scheduler
, 2004
"... Multimedia PCs run a diverse mix of multimedia, interactive, and batch applications. To better support the variety of realtime requirements generated by this application mix, multimedia PCs are evolving from soft to firm realtime systems. The hallmark of a firm realtime system is its ability to ..."
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Multimedia PCs run a diverse mix of multimedia, interactive, and batch applications. To better support the variety of realtime requirements generated by this application mix, multimedia PCs are evolving from soft to firm realtime systems. The hallmark of a firm realtime system is its ability to provide predictability to the user and applications. Sharebased CPU schedulers provide predictable CPU service to applications by allowing fractions of the CPU to be reserved on their behalf; if the share of an application is k, and the sum of all application shares is n, then the application receives at least k/n of the CPU capacity. Sharebased CPU schedulers are frequently proposed for use in multimedia systems. A challenge facing the user of a sharebased CPU scheduler is to select a share value for every application so that the application receives sufficient resources to help the user accomplish his goals. Finding the optimal share assignment is NPhard, implying that many choices of application shares will be less than optimal in practice. This thesis argues that a multimedia CPU scheduler must gracefully
A Bayesian System for Integration of Algorithms for RealTime Bayesian Network Inference
, 2002
"... Bayesian networks (BNs) are a key method for representation and reasoning under uncertainty in artificial intelligence. Both exact and approximate BN inference have been proven to be NPhard. The problems of inference become even less tractable under realtime constraints. One solution to realtime ..."
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Bayesian networks (BNs) are a key method for representation and reasoning under uncertainty in artificial intelligence. Both exact and approximate BN inference have been proven to be NPhard. The problems of inference become even less tractable under realtime constraints. One solution to realtime AI problems is to develop anytime algorithms. Anytime algorithms are iterative refinement algorithms that trade performance for time. They improve the quality of the output as the amount of time increases. Another solution to realtime AI consists of metareasoning and integrating multiple approximation methods. To date, researchers have developed various exact and approximate BN inference algorithms. Each of these has different properties and works better for different classes of inference problems. Given a BN inference problem instance, it is usually hard but important to decide in advance which algorithm among a set of choices is the most appropriate. This problem is known as the algorithm selection problem. This dissertation proposal addresses the problem of realtime BN inference. It proposes work on both development of new anytime approximation algorithms and integration of multiple inference algorithms. Specifically, I first propose...