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Taming Heterogeneity  The Ptolemy Approach
, 2003
"... Modern embedded computing systems tend to be heterogeneous in the sense of being composed of subsystems with very different characteristics, which communicate and interact in a variety of wayssynchronous or asynchronous, buffered or unbuffered, etc. Obviously, when designing such systems, a mode ..."
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Cited by 135 (16 self)
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Modern embedded computing systems tend to be heterogeneous in the sense of being composed of subsystems with very different characteristics, which communicate and interact in a variety of wayssynchronous or asynchronous, buffered or unbuffered, etc. Obviously, when designing such systems, a modeling language needs to reflect this heterogeneity. Today's modeling environments usually offer a variant of what we call amorphous heterogeneity to address this problem. This paper argues that modeling systems in this manner leads to unexpected and hardtoanalyze interactions between the communication mechanisms and proposes a more structured approach to heterogeneity, called hierarchical heterogeneity to solve this problem. It proposes a model structure and semantic framework that support this form of heterogeneity, and discusses the issues arising from heterogeneous component interaction and the desire for component reuse. It introduces the notion of domain polymorphism as a way to address these issues.
Heterogeneous Concurrent Modeling and Design in Java (Volumes 1: Introduction to Ptolemy II)
, 2005
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Embedded Software
 Advances in Computers
, 2002
"... The science of computation has systematically abstracted away the physical world. Embedded software systems, however, engage the physical world. Time, concurrency, liveness, robustness, continuums, reactivity, and resource management must be remarried to computation. Prevailing abstractions of compu ..."
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Cited by 53 (7 self)
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The science of computation has systematically abstracted away the physical world. Embedded software systems, however, engage the physical world. Time, concurrency, liveness, robustness, continuums, reactivity, and resource management must be remarried to computation. Prevailing abstractions of computational systems leave out these "nonfunctional" aspects. This chapter explains why embedded software is not just software on small computers, and why it therefore needs fundamentally new views of computation. It suggests component architectures based on a principle called "actororiented design," where actors interact according to a model of computation, and describes some models of computation that are suitable for embedded software. It then suggests that actors can define interfaces that declare dynamic aspects that are essential to embedded software, such as temporal properties. These interfaces can be structured in a "systemlevel type system" that supports the sort of designtime and runtime type checking that conventional software benefits from.
A Matlab Toolbox for RealTime and Control Systems CoDesign
"... The paper presents a Matlab toolbox for simulation of realtime control systems. The basic idea is to simulate a realtime kernel in parallel with continuous plant dynamics. The toolbox allows the user to explore the timely behavior of control algorithms, and to study the interaction between the con ..."
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Cited by 32 (7 self)
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The paper presents a Matlab toolbox for simulation of realtime control systems. The basic idea is to simulate a realtime kernel in parallel with continuous plant dynamics. The toolbox allows the user to explore the timely behavior of control algorithms, and to study the interaction between the control tasks and the scheduler. From a research perspective, it also becomes possible to experiment with more flexible approaches to realtime control systems, such as feedback scheduling. The importance of a more unified approach for the design of realtime control systems is discussed. The implementation is described in some detail and a number of examples are given.
Ptolemy II: Heterogeneous Concurrent Modeling and Design in Java
, 1999
"... This document describes Ptolemy II version 0.3. It contains three parts. The first part is a user's guide, which begins with an overview of the objectives of the software, then explains how to construct applets and applications, then reviews the actor libraries, and then concludes with a tutori ..."
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Cited by 23 (1 self)
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This document describes Ptolemy II version 0.3. It contains three parts. The first part is a user's guide, which begins with an overview of the objectives of the software, then explains how to construct applets and applications, then reviews the actor libraries, and then concludes with a tutorial on writing actors. The second part documents the software infrastructure. It is meant to complement, not replace, the code documentation. The third part documents the domains that have been written so far. Ptolemy II supports heterogeneous modeling and design of concurrent systems. It is component technology, in that the models are built by interconnecting components. Executable models are constructed under a model of computation, which is the set of "laws of physics" that govern the interaction of components in the model. If the model is describing a mechanical system, then the model of computation may literally be the laws of physics. More commonly, however, it is a set of rules that are more abstract, and provide a framework within which a designer builds models. A set of rules that govern the interaction of components is called the semantics of the model of computation. Each domain implements such a set of rules. Ptolemy II is written entirely in Java, and aims to support the construction of applets, servlets, migrating code, and embedded Java.
A hierarchical hybrid system model and its simulation
 In 38th IEEE conference on Decision and Control
, 1999
"... This paper presents a hierarchical hybrid system modeling and simulation framework using the Ptolemy I1 environment. Ptolemy I1 is a systemlevel design tool that supports the integration of multiple models of computation. The modeling of hierarchical hybrid systems is achieved by combining continu ..."
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Cited by 10 (3 self)
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This paper presents a hierarchical hybrid system modeling and simulation framework using the Ptolemy I1 environment. Ptolemy I1 is a systemlevel design tool that supports the integration of multiple models of computation. The modeling of hierarchical hybrid systems is achieved by combining continuoustime models with finite state automata. Breakpoint handling, event detection and invariant monitoring techniques are studied. A hybrid helicopter control system is simulated as an example. 1.
Interoperation of heterogeneous CAD tools in Ptolemy II
 In Proc. SPIE Vol. 3680, Design, Test, and Microfabrication of MEMS and MOEMS
, 1999
"... Typical complex systems that involve microsensors and microactuators exhibit heterogeneity both at the implementation level and the problem level. This naturally leads to a heterogeneous approach to system design that uses domainspecific models of computation (MoC) at various levels of abstractions ..."
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Cited by 2 (1 self)
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Typical complex systems that involve microsensors and microactuators exhibit heterogeneity both at the implementation level and the problem level. This naturally leads to a heterogeneous approach to system design that uses domainspecific models of computation (MoC) at various levels of abstractions to define a system, and leverages multiple CAD tools to do simulation, verification, and synthesis. As the size and scope of the system increases, the integration becomes too difficult and unmanageable if different tools are coordinated using simple scripts. In addition, for MEMS devices and mixedsignal circuits, it is essential to integrate tools with different MoCs to simulate the whole system. Ptolemy II, a heterogeneous systemlevel design tool, supports the interaction among different MoCs. This paper discusses heterogeneous CAD tool interoperability in the Ptolemy II framework. The key is to understand the semantic interface and classify the tools by their MoC and their level of abstraction. Interfaces are designed for each domain so that the external tools can be easily wrapped. Then the interoperability of the tools becomes the interoperability of the domains. Ptolemy II can serve as the standard interface among different tools to achieve overall design modeling. A microaccelerometer with digital feedback is studied as an example.
MULTIFORMALISM MODELLING AND MODEL EXECUTION
"... Modelling complex software systems requires multiple modelling formalisms adapted to the nature of each part of the system (control, signal processing, etc.), to the aspect on which the model focuses (functionality, time, fault tolerance, etc.) and to the level of abstraction at which the system, or ..."
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Cited by 1 (0 self)
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Modelling complex software systems requires multiple modelling formalisms adapted to the nature of each part of the system (control, signal processing, etc.), to the aspect on which the model focuses (functionality, time, fault tolerance, etc.) and to the level of abstraction at which the system, or one of its parts, is studied. The use of different modelling formalisms during the development cycle is therefore both unavoidable and essential. As a consequence, system designers deal with a large variety of models that relate to a given system but do not form a global model of this system. A major difficulty is then to answer questions about properties of the whole system, and in particular about its behaviour. MultiFormalism Modelling allows the joint use of different modelling formalisms in a given model to overcome issues related to the integration of heterogeneous models. It applies to different tasks of the development cycle such as simulation, verification or testing. 1 We propose an approach to multiformalism modelling, called ModHel’X, which is based on the concept of Model of Computation and focuses on the simulation of models. Our approach addresses two important issues in this particular field: (a) providing support for the specification of the execution semantics of a modelling formalism, and (b) allowing the specification of the interactions between parts of a model described using different modelling formalisms. Key Words Multiformalism modelling, heterogeneous modelling, model of computation, simulation of heterogeneous models, modeldriven engineering