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Simulating Concurrent Behaviors with WorstCase Cost Bounds ⋆
"... Abstract. Modern software systems are increasingly being developed for deployment on a range of architectures. For this purpose, it is interesting to capture aspects of lowlevel deployment concerns in highlevel modeling languages. In this paper, an executable objectoriented modeling language is e ..."
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Abstract. Modern software systems are increasingly being developed for deployment on a range of architectures. For this purpose, it is interesting to capture aspects of lowlevel deployment concerns in highlevel modeling languages. In this paper, an executable objectoriented modeling language is extended with resourcerestricted deployment components. To analyze model behavior a formal methodology is proposed to assess resource consumption, which balances the scalability of the method and the reliability of the obtained results. The approach applies to a general notion of resource, including traditional cost measures (e.g., time, memory) as well as concurrencyrelated measures (e.g., requests to a server, spawned tasks). The main idea of our approach is to combine reliable (but expensive) worstcase cost analysis of statically predictable parts of the model with fast (but inherently incomplete) simulations of the concurrent aspects in order to avoid the statespace explosion. The approach is illustrated by the analysis of memory consumption. 1
Performance Analysis of Reconfiguration in Adaptive RealTime Streaming Applications
"... We propose a design optimization framework for adaptive realtime streaming applications. The main contribution is a hybrid approach for performance analysis combining formal analysis and simulation using a twophase framework. We formulate the scheduling problem of adaptive streaming applications w ..."
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Cited by 3 (3 self)
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We propose a design optimization framework for adaptive realtime streaming applications. The main contribution is a hybrid approach for performance analysis combining formal analysis and simulation using a twophase framework. We formulate the scheduling problem of adaptive streaming applications with ILP analysis, and use the simulation based on the synchronous model of computation to ensure throughput guarantees. We finally illustrate the capabilities of our methodology by experiments. 1.
Arrival Curves for RealTime Calculus: the Causality Problem and its Solutions
"... Abstract. The RealTime Calculus (RTC) [16] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by pairs of curves, called arrival curves, that express upper and lower bounds on the number of events that may arrive over any spec ..."
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Abstract. The RealTime Calculus (RTC) [16] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by pairs of curves, called arrival curves, that express upper and lower bounds on the number of events that may arrive over any specified time interval. System properties may then be computed using algebraic techniques in a compositional way. A wellknown limitation of RTC is that it cannot model systems with states and recent works [7, 1, 13, 11] studied how to interface RTC curves with statebased models. Doing so, while trying, for example to generate a stream of events that satisfies some given pair of curves, we faced a causality problem [14]: it can be the case that, once having generated a finite prefix of an event stream, the generator deadlocks, since no extension of the prefix can satisfy the curves anymore. When trying to express the property of the curves with statebased models, one may face the same problem. This paper formally defines the problem on arrival curves, and gives algebraic ways to characterize causal pairs of curves, i.e. curves for which the problem cannot occur. Then, we provide algorithms to compute a causal pair of curves equivalent to a given curve, in several models. These algorithms provide a canonical representation for a pair of curves, which is the best pair of curves among the curves equivalent to the ones they take as input. 1
Compositional Timing Analysis
"... We develop and implement a methodology for automatic abstraction of systems defined as networks of timed components modeled by timed automata. The abstraction technique yields an abstract model with much less clocks and states which overapproximate the timed behavior of the concrete system. Using th ..."
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Cited by 2 (0 self)
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We develop and implement a methodology for automatic abstraction of systems defined as networks of timed components modeled by timed automata. The abstraction technique yields an abstract model with much less clocks and states which overapproximate the timed behavior of the concrete system. Using this technique we can analyze timed system of size beyond the capabilities of contemporary analysis tools for timed automata.
Causality Closure for a New Class of Curves in RealTime Calculus
"... RealTime Calculus (RTC) [14] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by arrival curves which express upper and lower bounds on the number of events that may arrive over any specified time interval. System properties ..."
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Cited by 1 (1 self)
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RealTime Calculus (RTC) [14] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by arrival curves which express upper and lower bounds on the number of events that may arrive over any specified time interval. System properties may then be computed using algebraic techniques in a compositional way. The property of causality on arrival curves essentially characterizes the absence of deadlock in the corresponding generator. A mathematical operation called causality closure transforms arbitrary curves into causal ones. In this paper, we extend the existing theory on causality to the class Upac of infinite curves represented by a finite set of points plus piecewise affine functions, where existing algorithms did not apply. We show how to apply the causality closure on this class of curves, prove that this causal representative is still in the class and give algorithms to compute it. This provides the tightest pair of curves among the curves which accept the same sets of streams.
(2011)" DOI: 10.1145/2071589.2071590 Causality Closure for a New Class of Curves in RealTime Calculus
, 2011
"... RealTime Calculus (RTC) [14] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by arrival curves which express upper and lower bounds on the number of events that may arrive over any specified time interval. System properties ..."
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RealTime Calculus (RTC) [14] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by arrival curves which express upper and lower bounds on the number of events that may arrive over any specified time interval. System properties may then be computed using algebraic techniques in a compositional way. The property of causality on arrival curves essentially characterizes the absence of deadlock in the corresponding generator. A mathematical operation called causality closure transforms arbitrary curves into causal ones. In this paper, we extend the existing theory on causality to the class Upac of infinite curves represented by a finite set of points plus piecewise affine functions, where existing algorithms did not apply. We show how to apply the causality closure on this class of curves, prove that this causal representative is still in the class and give algorithms to compute it. This provides the tightest pair of curves among the curves which accept the same sets of streams.
Accurate Runtime Performance Prediction for MultiApplication MultiProcessor Systems
"... Abstract — Nonpreemptive multiprocessor platforms are increasingly being developed to support the performance requirements of modern systems with multiple applications. Due to a huge number of possible combinations of these multiple applications, it becomes a challenge to predict their performance ..."
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Abstract — Nonpreemptive multiprocessor platforms are increasingly being developed to support the performance requirements of modern systems with multiple applications. Due to a huge number of possible combinations of these multiple applications, it becomes a challenge to predict their performance in advance. This becomes even more important when applications may be dynamically started and stopped in the system. Misprediction may result in reduced quality of applications and lower the userexperience. Since modern embedded systems allow users to download and add applications at runtime, a complete designtime analysis is not possible. In this paper, we present a technique to accurately predict the performance of applications at runtime before they execute in the system. The technique uses performance expressions computed offline from the application specifications. A runtime iterative
Iterative Probabilistic Performance Prediction for MultiApplication Multiprocessor Systems
"... Abstract—Modern embedded devices are increasingly becoming multiprocessor with the need to support a large number of applications to satisfy the demands of users. Due to a huge number of possible combinations of these multiple applications, it becomes a challenge to predict their performance. This b ..."
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Abstract—Modern embedded devices are increasingly becoming multiprocessor with the need to support a large number of applications to satisfy the demands of users. Due to a huge number of possible combinations of these multiple applications, it becomes a challenge to predict their performance. This becomes even more important when applications may be dynamically started and stopped in the system. Since modern embedded systems allow users to download and add applications at runtime, a complete designtime analysis is not always possible. This paper presents a new technique to accurately predict the performance of multiple applications mapped on a multiprocessor platform. Iterative probabilistic analysis is used to estimate the time spent by tasks during their contention phase, and thereby predicting the performance of applications. The approach is scalable with the number of applications and processors in the system. As compared to earlier techniques, this approach is much faster and scalable, while still improving the accuracy. The analysis takes 300 µs on a 500 MHz processor for ten applications. Since multimedia applications are increasingly becoming more dynamic, results of a casestudy with applications with varying execution times are also presented. In addition, results of a casestudy with real applications executing on a fieldprogrammable gate array multiprocessor platform are shown. Index Terms—Heterogeneous multiprocessor, multiple applications, nonpreemption, performance prediction, synchronous data flow graphs. I.
ARRIVAL AND DELAY CURVE ESTIMATION FOR SLA Calculus
"... An algorithm and selection method to estimate Network Calculus arrival bounds for systems with concurrent arrivals is presented. Concurrent job arrivals are common for ServiceOriented Architectures. Their performance is described in Service Level Agreements including quantitative requirements for l ..."
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An algorithm and selection method to estimate Network Calculus arrival bounds for systems with concurrent arrivals is presented. Concurrent job arrivals are common for ServiceOriented Architectures. Their performance is described in Service Level Agreements including quantitative requirements for load and response times. SLA Calculus, a variant of Network Calculus, can be used for service performance modeling and validation with SLAs. Functions called curves are used to bound job arrivals as well as their delay. Due to the concurrent nature of job arrivals curve estimation methods used for successive packet arrivals in Network Calculus cannot be applied in SLA Calculus. We present a method to estimate unknown SLA Calculus arrival and delay bounds from input and output traces. This paper introduces an algorithm for the estimation of the curves. Optimal selection of a curve model based on several fitting criteria is performed using candidates from trace sets. 1