ArtistDesign NoE

Languages and Tools for Hybrid Systems Design

Alberto Sangiovanni-Vincentelli — 2006-08-31T09:43:38Z

Luca P. Carloni (Columbia University)
Roberto Passerone (Cadence, UC Berkeley)
Alessandro Pinto (UC Berkeley)
Alberto L. Sangiovanni-Vincentelli (Parades/UC Berkeley)

In this paper, we collected data on available languages, formalism and tools that have been proposed in the past years for the design and verification of hybrid systems.

We review and compare these tools by highlighting their differences in the underlying semantics, expressive power and solution mechanisms.

Abstract
The explosive growth of embedded electronics is bringing information and control systems of increasing complexity to every aspects of our lives. The most challenging designs are safety-critical systems, such as transportation systems (e.g., airplanes, cars, and trains), industrial plants and health care monitoring. The difficulties reside in accommodating constraints both on functionality and implementation. The correct behavior must be guaranteed under diverse states of the environment and potential failures; implementation has to meet cost, size, and power consumption requirements. The design is therefore subject to extensive mathematical analysis and simulation. However, traditional models of information systems do not interface well to the continuous evolving nature of the environment in which these devices operate. Thus, in practice, different mathematical representations have to be mixed to analyze the overall behavior of the system. Hybrid systems are a particular class of mixed models that focus on the combination of discrete and continuous subsystems. There is a wealth of tools and languages that have been proposed over the years to handle hybrid systems. However, each tool makes different assumptions on the environment, resulting in somewhat different notions of hybrid system. This makes it difficult to share information among tools. Thus, the community cannot maximally leverage the substantial amount of work that has been directed to this important topic. In this paper, we review and compare hybrid system tools by highlighting their differences in terms of their underlying semantics, expressive power and mathematical mechanisms. We conclude our review with a comparative summary, which suggests the need for a unifying approach to hybrid systems design. As a step in this direction, we make the case for a semantic-aware interchange format, which would enable the use of joint techniques, make a formal comparison between different approaches possible, and facilitate exporting and importing design representations.

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ACM - Special Issue on Education

Alan Burns, Alberto Sangiovanni-Vincentelli — 2006-08-31T08:54:04Z

Guest Editors Alan Burns - University of York Alberto Sangiovanni-Vincentelli - UC Berkeley

Embedded systems applications now include a very large proportion of the advanced products designed in the world, spanning transport (avionics, space, automotive, trains), electrical and electronic appliances (cameras, toys, television, washers, dryers, audio systems, and cellular phones), process control (energy production and distribution, factory automation and optimization), telecommunications (satellites, mobile phones and telecom networks), and security (e-commerce, smart cards), etc.. The relative weight of software in the value of embedded systems is constantly expanding. The extensive and increasing use of embedded systems and their integration in everyday products marks a significant evolution in information science and technology.

There is now a strategic shift in emphasis for embedded systems designers: from simply achieving feasibility, to achieving optimality. Optimal design of embedded systems means targeting a given market segment at the lowest cost and delivery time possible. Optimality means seamless integration with the physical and electronic environment while respecting real-world constraints such as hard deadlines, reliability, availability, robustness, power consumption, and cost. In our view, optimality can only be achieved through the emergence of embedded systems as a discipline in its own right.

An important factor for the emergence of embedded systems as a discipline is the existence of integrated curricula for training engineers and researchers, able to tackle a range of topics which until now had been spread across many different areas, including: general computer science and engineering, real-time computing, systems architecture, control and signal processing, security and privacy, networking, mathematics, electronics.

This special issue of the ACM Transactions in Embedded Computing Systems aims to provide the basis for integrated undergraduate and graduate curricula covering the essential areas of knowledge for tomorrow's embedded systems engineers and researchers.

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Access the ACM TECS page here.

ACM Transactions in Embedded Computing Systems - Special Issue on Education

Alan Burns, Alberto Sangiovanni-Vincentelli — 2006-08-25T14:32:04Z

Guest Editors: Alan Burns, Alberto Sangiovanni-Vincentelli Topics: Education for Embedded Systems Design

Embedded systems applications now include a very large proportion of the advanced products designed in the world, spanning transport (avionics, space, automotive, trains), electrical and electronic appliances (cameras, toys, television, washers, dryers, audio systems, and cellular phones), process control (energy production and distribution, factory automation and optimization), telecommunications (satellites, mobile phones and telecom networks), and security (e-commerce, smart cards), etc.. The relative weight of software in the value of embedded systems is constantly expanding. The extensive and increasing use of embedded systems and their integration in everyday products marks a significant evolution in information science and technology.

There is now a strategic shift in emphasis for embedded systems designers: from simply achieving feasibility, to achieving optimality. Optimal design of embedded systems means targeting a given market segment at the lowest cost and delivery time possible. Optimality means seamless integration with the physical and electronic environment while respecting real-world constraints such as hard deadlines, reliability, availability, robustness, power consumption, and cost. In our view, optimality can only be achieved through the emergence of embedded systems as a discipline in its own right.

An important factor for the emergence of embedded systems as a discipline is the existence of integrated curricula for training engineers and researchers, able to tackle a range of topics which until now had been spread across many different areas, including: general computer science and engineering, real-time computing, systems architecture, control and signal processing, security and privacy, networking, mathematics, electronics.

This special issue of the ACM Transactions in Embedded Computing Systems aims to provide the basis for integrated undergraduate and graduate curricula covering the essential areas of knowledge for tomorrow's embedded systems engineers and researchers.

Languages and Tools for Hybrid Systems

Alberto Sangiovanni-Vincentelli — 2006-08-25T14:10:58Z

Authors: Luca P. Carloni, Roberto Passerone, Alessandro Pinto and Alberto L. Sangiovanni-Vincentelli

In this paper, we collected data on available languages, formalism and tools that have been proposed in the past years for the design and verification of hybrid systems. We review and compare these tools by highlighting their differences in the underlying semantics, expressive power and solution mechanisms. Table 1 lists tools and languages reviewed in this paper with information on the institution that supports the development of each project as well as pointers to the corresponding web site 1 and to some relevant publications.
The tools are covered in two main sections: one dedicated to simulationcentric tools including commercial offerings, one dedicated to formal verification-centric tools. The simulation-centric tools are the most popular among designers as they pose the least number of constraints on the systems to be analyzed. On the other hand, their semantics are too general to be amenable to formal analysis or synthesis. Tools based on restricted expressiveness of the description languages (see, for example, the synthesizable subset of RTL languages as a way of allowing tools to operate on a more formal way that may yield substantial productivity gains) do have an appeal as they may be the ones to provide the competitive edge in terms of quality of results and cost for obtaining them. The essence is to balance the gains in analysis and synthesis power versus the loss of expressive power.

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Sangiovanni-Vincentelli

Alberto Sangiovanni-Vincentelli — 2006-07-31T15:00:36Z

- 30. Core Team Leaders / Real-Time Components, Strategic Management Board, Strategic Management Board, Modeling and Validation, Intercluster activity: Design for Predictability and Performance, Intercluster activity: Integration Driven by Industrial Applications

30. Real Time Systems

2006-07-04T08:11:07Z

The journal Real-Time Systems publishes papers that concentrate on real-time computing principles and applications, which may be research papers, invited papers, project reports and case studies, standards and corresponding proposals for general discussion, and a partitioned tutorial on real-time systems as a continuing series. Much of the work in building sophisticated, modern real-time systems is interdisciplinary in nature and is often found scattered throughout the primary literature.

Real-Time Systems provides a single-source coverage of the state of the art in this exciting and expanding field. The editorial board, the writers and the readers of the journal are drawn from all parts of the world, from industry, and from academia.

Papers published in Real-Time Systems cover, among others, the following topics: requirements engineering, specification and verification techniques, design methods and tools, programming languages, operating systems, scheduling algorithms, architecture, hardware and interfacing, dependability and safety, distributed and other novel architectures, wired and wireless communications, wireless sensor systems, distributed databases, artificial intelligence techniques, expert systems, and application case studies. Applications are found in command and control systems, process control, automated manufacturing, flight control, avionics, space avionics and defense systems], shipborne systems, vision and robotics, pervasive and ubiquitous computing, and in an abundance of embedded systems.

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