Thomas E. Bihari

Dynamic adaptation of real-time software

In large, dynamic, real-time computer systems, it is frequently most cost effective to employ different software performance and reliability techniques at different levels of granularity, at different times, or within different subsystems. These techniques may include regulation of redundancy and resource allocation, multiversion and multipath execution, adjustments of program attributes such as time-out periods and others. The management of software in such systems is a difficult task. Software that may be adapted to meet varying performance and reliability requirements offers a solution. A REal-time Software Adaptation System (RESAS) includes a uniform model of adaptable software and provides the tool necessary for programmers to implement algorithms that choose and enact adaptations in real time. RESAS has been implemented on a testbed consisting of a multiprocessor and an attached workstation, and adaptation algorithms have been developed that address the problem of adapting software to achieve two goals: software execution within specified time constraints and software resiliency with respect to computer hardware failures.

High-performance operating system primitives for robotics and real-time control systems

To increase speed and reliability of operation, multiple computers are replacing uniprocessors and wired-logic controllers in modern robots and industrial control systems. However, performance increases are not attained by such hardware alone. The operating software controlling the robots or control systems must exploit the possible parallelism of various control tasks in order to perform the necessary computations within given real-time and reliability constraints. Such software consists of both control programs written by application programmers and operating system software offering means of task scheduling, intertask communication, and device control. The Generalized Executive for real-time Multiprocessor applications (GEM) is an operating system that addresses several requirements of operating software. First, when using GEM, programmers can select one of two different types of tasks differing in size, called processes and microprocesses. Second, the scheduling calls offered by GEM permit the implementation of several models of task interaction. Third, GEM supports multiple models of communication with a parameterized communication mechanism. Fourth, GEM is closely coupled to prototype real-time programming environments that provide programming support for the models of computation offered by the operating system. GEM is being used on a multiprocessor with robotics application software of substantial size and complexity.

Object-oriented real-time systems: concepts and examples

The problems associated with developing real-time software systems, including ensuring predictable real-time behavior under both normal and abnormal operating conditions, are outlined. The management of temporal complexity, structuring of dynamic real-time applications, object-oriented models, object-oriented real-time languages, and the requirements for real-time object-oriented models are discussed. Chaos, an object-based language and programming/execution paradigm designed for dynamic real-time applications, is described.<<ETX>>

Object-oriented design of real-time software

An examination is made of the ability of the object-oriented model to represent and encapsulate the temporal characteristics of adaptable, real-time software. The differences between object-oriented design and the more traditional function-oriented design of real-time systems are briefly reviewed. The various temporal characteristics present in a real-time, object-oriented system and techniques for the design of object-oriented real-time software are examined. The many open problems in the area are discussed. The object-oriented model and many of the concepts described have been used in the implementation of the control software for an experimental robotics project.<<ETX>>

A comparison of four adaptation algorithms for increasing the reliability of real-time software

In a large, parallel, real-time computer system, it is frequently most cost-effective to use different software reliability techniques (e.g., retry, replication, and resource-allocation algorithms) at different levels of granularity or within different subsystems, dependent on the reliability requirements and fault models associated with each subsystem. The authors describe the results of applying four reliability algorithms, via RESAS (REal-time Software Adaptation System), to a sample real-time program executing on a multiprocessor.<<ETX>>

GEM: Operating system primitives for robots and real-time control systems

To increase the speed and reliability of robots and of industrial control systems, multiple processing elements are used in their computing hardware. However, performance increases are not attained by hardware, alone. It is the hardwares operating software that must exploit the possible parallelism to gain the increases desired. Such software consists of control programs written by application programmers and operating system software offering means of task scheduling, inter-task communication, and hardware configuration control. The Generalized Executive for real-time Multiprocessor applications (GEM) is an operating system that addresses several problems arising due to the unique requirements of operating software, including: (1) GEM supports two different sizes of tasks and task scheduling, called processes and micro-processes, and offers a variety of real-time scheduling calls, and (2) GEM supports multiple models of communication.

Providing end-to-end perspectives in software engineering

In order to better prepare students for professional practice, we have created a software engineering curriculum that provides an end-to-end perspective that begins with the business context of software, and goes all the way to the ongoing management of software services after deployment. This paper examines how the theoretical aspects of this broad-based curriculum may be effectively delivered through a single course within a traditional computer science program. This curriculum is under a diverse set of constraints and requirements, such as the need for pedagogical consistency, faculty development, consideration of the learning style of computer science students, and a need for an effective continuous improvement process. Our approach uses “engineering-oriented” analysis frameworks such as Porters Five Forces model for the business aspects, and attribute-driven design for software architectures, an “inverted” classroom mode of teaching where lectures are delivered on line with interactions and exercises that promote active learning reserved for the classroom, case studies developed from real projects to serve as concrete examples, open discussion boards and weekly short quizzes for concept refinement and retention, and a paper-based project where students apply the concepts learned. Faculty development and replication outside the current site are also discussed.

Enabling scalability, richer experiences and ABET-accreditable learning outcomes in computer science Capstone courses through inversion of control

Capstone courses are expected to prepare students for the “real world” by putting them into a microcosm of the real world. In these courses, students are given a problem of some complexity, and are expected to exercise and develop problem-solving skills as they address the problem. Within our Computer Science and Engineering program we have, over the past eight years, successfully scaled up the Capstone courses. Doing so has required innovative thinking about the roles of the students, faculty, and project sponsors. In this paper, we discuss issues with scaling up the components that have made this program successful. These include housing the courses in an NSF IUCRC that enable the cultivation of highly-committed industry partners, the creation of strong pre-requisite courses, careful development of faculty resources through the selective hiring and mentoring of clinical faculty, a commitment of the faculty to give up close management and control, strong partnerships with other organizations within the university to provide students greater access to resources, an emphasis on cross-team knowledge sharing and learning, and the development of unique assessment and evaluation tools so as to be able to monitor, measure and fairly assess a wide-spectrum of projects.