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An overview of competitive and adversarial approaches to designing dynamic power management strategies
 IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
, 2005
"... Dynamic power management (DPM) refers to the problem of judicious application of various lowpower techniques based on runtime conditions in an embedded system to minimize the total energy consumption. To be effective, often such decisions take into account the operating conditions and the systeml ..."
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Dynamic power management (DPM) refers to the problem of judicious application of various lowpower techniques based on runtime conditions in an embedded system to minimize the total energy consumption. To be effective, often such decisions take into account the operating conditions and the systemlevel design goals. DPM has been a subject of intense research in the past decade driven by the need for low power consumption in modern embedded devices. We present a comprehensive overview of two closely related approaches to designing DPM strategies, namely, competitive analysis approach and model checking approach based on adversarial modeling. Although many other approaches exist for solving the systemlevel DPM problem, these two approaches are closely related and are based on a common theme. This commonality is in the fact that the underlying model is that of a competition between the system and an adversary. The environment that puts service demands on devices is viewed as an adversary, or to be in competition with the system to make it burn more energy, and the DPM strategy is employed by the system to counter that.
Probabilistic Model Checking for Systems Biology
"... Probabilistic model checking is a technique for formally verifying quantitative properties of systems that exhibit stochastic behaviour. In this chapter, we show how this approach can be applied to the study of biological systems such as biochemical reaction networks and signalling pathways. We p ..."
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Cited by 15 (1 self)
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Probabilistic model checking is a technique for formally verifying quantitative properties of systems that exhibit stochastic behaviour. In this chapter, we show how this approach can be applied to the study of biological systems such as biochemical reaction networks and signalling pathways. We present an introduction to the stateoftheart probabilistic model checking tool PRISM using a case study based on the Fibroblast Growth Factor (FGF) signalling pathway.
A Symbolic OutofCore Solution Method for Markov Models
 In Proc. Workshop on Parallel and Distributed Model Checking (PDMC'02), volume 68.4 of Electronic Notes in Theoretical Computer Science
, 2002
"... Despite considerable eort, the statespace explosion problem remains an issue in the analysis of Markov models. Given structure, symbolic representations can result in very compact encoding of the models. However, a major obstacle for symbolic methods is the need to store the probability vector(s) e ..."
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Cited by 14 (11 self)
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Despite considerable eort, the statespace explosion problem remains an issue in the analysis of Markov models. Given structure, symbolic representations can result in very compact encoding of the models. However, a major obstacle for symbolic methods is the need to store the probability vector(s) explicitly in main memory. In this paper, we present a novel algorithm which relaxes these memory limitations by storing the probability vector on disk. The algorithm has been implemented using an MTBDDbased data structure to store the matrix and an array to store the vector. We report on experimental results for two benchmark models, a Kanban manufacturing system and a exible manufacturing system, with models as large as 133 million states.
Evaluating the reliability of NAND multiplexing with PRISM
 IEEE TRANSACTIONS ON COMPUTERAIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
, 2005
"... Probabilistic model checking is a formal verification technique for analysing the reliability and performance of systems exhibiting stochastic behaviour. In this paper, we demonstrate the applicability of this approach and, in particular, the probabilistic model checking tool PRISM to the evaluati ..."
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Cited by 14 (4 self)
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Probabilistic model checking is a formal verification technique for analysing the reliability and performance of systems exhibiting stochastic behaviour. In this paper, we demonstrate the applicability of this approach and, in particular, the probabilistic model checking tool PRISM to the evaluation of reliability and redundancy of defecttolerant systems in the field of computeraided design. We illustrate the technique with an example due to von Neumann, namely NAND multiplexing. We show how, having constructed a model of a defecttolerant system incorporating probabilistic assumptions about its defects, it is straightforward to compute a range of reliability measures and investigate how they are affected by slight variations in the behaviour of the system. This allows a designer to evaluate, for example, the tradeoff between redundancy and reliability in the design. We also highlight errors in analytically computed reliability bounds, recently published for the same case study.
CSL model checking of biochemical networks with interval decision diagrams
 in Proc. CMSB 2009. LNCS/LNBI 5688
, 2009
"... Abstract. This paper presents an Interval Decision Diagram based approach to symbolic CSL model checking of Continuous Time Markov Chains which are derived from stochastic Petri nets. Matrixvector and vectormatrix multiplication are the major tasks of exact analysis. We introduce a simple, but po ..."
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Abstract. This paper presents an Interval Decision Diagram based approach to symbolic CSL model checking of Continuous Time Markov Chains which are derived from stochastic Petri nets. Matrixvector and vectormatrix multiplication are the major tasks of exact analysis. We introduce a simple, but powerful algorithm which uses explicitly the Petri net structure and allows for parallelisation. We present results demonstrating the efficiency of our first prototype implementation when applied to biochemical network models, specifically with increasing token numbers. Our tool currently supports CSL model checking of timebounded operators and the Next operator for ordinary stochastic Petri nets. 1
Probabilistic Analysis using Theorem Proving
"... Abstract. Traditionally, computer simulation techniques are used to perform probabilistic analysis. However, they provide less accurate results and cannot handle largescale problems due to their enormous CPU time requirements. Recently, a significant amount of formalization has been done in the HOL ..."
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Abstract. Traditionally, computer simulation techniques are used to perform probabilistic analysis. However, they provide less accurate results and cannot handle largescale problems due to their enormous CPU time requirements. Recently, a significant amount of formalization has been done in the HOL theorem prover that allows us to conduct precise probabilistic analysis using theorem proving and thus overcome the limitations of the simulation based probabilistic analysis approach. Some major contributions include the formalization of both discrete and continuous random variables and the verification of some of their corresponding probabilistic and statistical properties. This paper presents a concise description of the infrastructures behind these capabilities and the utilization of these features to conduct the probabilistic analysis of realworld systems. For illustration purposes, the paper describes the theorem proving based probabilistic analysis of three examples, i.e., the roundoff error of a digital processor, the Coupon Collector’s problem and the StopandWait protocol. 1
Snoopy  a tool to design and animate/simulate graphbased formalisms
 IN: PROC. PNTAP 2008, ASSOCIATED TO SIMUTOOLS 2008. ACM DIGITAL LIBRARY
, 2008
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Advances in Model Representations
 Proc. PAPM/PROBMIV 2001, Available as Volume 2165 of LNCS (2001
, 2001
"... We review highlevel specification formalisms for Markovian performability models, thereby emphasising the role of structuring concepts as realised par excellence by stochastic process algebras. Symbolic representations based on decision diagrams are presented, and it is shown that they quite id ..."
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Cited by 9 (4 self)
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We review highlevel specification formalisms for Markovian performability models, thereby emphasising the role of structuring concepts as realised par excellence by stochastic process algebras. Symbolic representations based on decision diagrams are presented, and it is shown that they quite ideally support compositional model construction and analysis.
Symbolic Performance and Dependability Evaluation with the Tool CASPA
 In FORTE Workshops, volume 3236 of LNCS
, 2004
"... This paper describes the tool CASPA,anewperformance evaluation tool which is based on a Markovian stochastic process algebra. ..."
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Cited by 8 (2 self)
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This paper describes the tool CASPA,anewperformance evaluation tool which is based on a Markovian stochastic process algebra.