Engineering topics
Publications and source records attributed to Hinchey, Michael G..
A memory apparatus includes a non-volatile computer memory, a USB mass storage controller connected to the non-volatile computer memory, the USB mass storage controller including a daisy chain component, a male USB interface connected to the USB mass storage controller, and at least one other interface for a memory device, other than a USB interface, the at least one other interface being connected to the USB mass storage controller.
Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required.
Systems, methods and apparatus are provided through which in some embodiments an autonomic entity manages a system by generating one or more stay alive signals based on the functioning status and operating state of the system. In some embodiments, an evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy. The evolvable neural interface receives and generates heartbeat monitor signals and pulse monitor signals that are used to generate a stay alive signal that is used to manage the operations of the synthetic neural system. In another embodiment an asynchronous Alice signal (Autonomic license) requiring valid credentials of an anonymous autonomous agent is initiated. An unsatisfactory Alice exchange may lead to self-destruction of the anonymous autonomous agent for self-protection.
The "Requirements-to-Design-to-Code" (R2D2C) project at NASA's Goddard Space Flight Center is based on deriving a formal specification expressed in Communicating Sequential Processes (CSP) notation from system requirements supplied in the form of CSP traces. The traces, in turn, are to be extracted from scenarios, a user-friendly medium often used to describe the required behavior of computer systems under development. This work, called Mise en Scene, defines a new scenario medium (Scenario Notation Language, SNL) suitable for control-dominated systems, coupled with a two-stage process for automatic translation of scenarios to a new trace medium (Trace Notation Language, TNL) that encompasses CSP traces. Mise en Scene is offered as an initial solution to the problem of the scenarios-to-traces "D2" phase of R2D2C. A survey of the "scenario" concept and some case studies are also provided.
Visions for future space exploration have long term science missions in sight, resulting in the need for sustainable missions. Survivability is a critical property of sustainable systems and may be addressed through autonomicity, an emerging paradigm for self-management of future computer-based systems based on inspiration from the human autonomic nervous system. This paper examines some of the ongoing research efforts to realize these survivable systems visions, with specific emphasis on developments in Autonomic Policies.
We view an evolutionary system ns being n software product line. The core architecture is the unchanging part of the system, and each version of the system may be viewed as a product from the product line. Each "product" may be described as the core architecture with sonre agent-based additions. The result is a multiagent system software product line. We describe an approach to such n Software Product Line-based approach using the MaCMAS Agent-Oriented nzethoclology. The approach scales to enterprise nrchitectures as a multiagent system is an approprinre means of representing a changing enterprise nrchitectclre nnd the inferaction between components in it.
Autonomic communications has been gaining ground as a vision for next generation communications. The success and flexibility of the Internet has lead to evaluations of utilizing IP for communications in space. The limitations of today's Internet ultimately also imply limitations for an IP deployment in space. Issues affecting the design of a future self-directing and self-managing data communications network for future space missions based on autonomic communications concepts are described and examined.
With NASA s renewed commitment to outer space exploration, greater emphasis is being placed on both human and robotic exploration. Even when humans are involved in the exploration, human tending of assets becomes cost-prohibitive or in many cases is simply not feasible. In addition, certain exploration missions will require spacecraft that will be capable of venturing where humans cannot be sent. Early space missions were operated manually from ground control centers with little or no automated operations. In the mid-l980s, the high costs of satellite operations prompted NASA, and others, to begin automating as many functions as possible. In our context, a system is autonomous if it can achieve its goals without human intervention. A number of more-or-less automated ground systems exist today, but work continues with the goal being to reduce operations costs to even lower levels. Cost reductions can be achieved in a number of areas. Ground control and spacecraft operations are two such areas where greater autonomy can reduce costs. As a consequence, autonomy is increasingly seen as a critical approach for robotic missions and for some aspects of manned missions. Although autonomy will be critical for the success of future missions (and indeed will enable certain kinds of science data gathering approaches), missions imbued with autonomy must also exhibit autonomic properties. Exploitation of autonomy alone, without emphasis on autonomic properties, will leave spacecraft vulnerable to the dangerous environments in which they must operate. Without autonomic properties, a spacecraft may be unable to recognize negative environmental effects on its components and subsystems, or may be unable to take any action to ameliorate the effects. The spacecraft, though operating autonomously, may then sustain a degradation of performance of components or subsystems, and consequently may have a reduced potential for achieving mission objectives. In extreme cases, lack of autonomic properties could leave the spacecraft unable to recover from faults. Ensuring that exploration spacecraft have autonomic properties will increase the survivability and therefore the likelihood of success of these missions. In fact, over time, as mission requirements increased demands on spacecraft capabilities and longevity, designers have gradually built more autonomicity into spacecraft. For example, a spacecraft in low-earth orbit may experience an out-of-bounds perturbation of its attitude (orientation) due to increased drag caused by increased atmospheric density at its altitude as a result of a sufficiently large solar flare. If the spacecraft was designed to recognize the excessive attitude perturbation, it could decide to protect itself by going into a safe-hold mode where its internal configuration and operation are altered to conserve power and its coarse attitude is adjusted to point its solar panels toward the Sun to maximize power generation. This is an example of a simple type of autonomic behavior that has actually occurred. Future mission concepts will be increasingly dependent on space system survivability enabled by more advanced types of autonomic behaviors
New processes, methods and tools are constantly appearing in the field of software engineering. Many of these augur great potential in improving software development processes, resulting in higher quality software with greater levels of assurance. However, there are a number of obstacles that impede their infusion into software development practices. These are the recurring obstacles common to many forms of research. Practitioners cannot readily identify the emerging techniques that may most benefit them, and cannot afford to risk time and effort in evaluating and experimenting with them while there is still uncertainty about whether they will have payoff in this particular context. Similarly, researchers cannot readily identify those practitioners whose problems would be amenable to their techniques and lack the feedback from practical applications necessary to help them to evolve their techniques to make them more likely to be successful. This paper describes an ongoing effort conducted by a software engineering research infusion team, and the NASA Research Infusion Initiative, established by NASA s Software Engineering Initiative, to overcome these obstacles.
The four key objective properties of a system that are required of it in order for it to qualify as "autonomic" are now well-accepted-self-configuring, self-healing, self-protecting, and self-optimizing- together with the attribute properties-viz. self-aware, environment-aware, self-monitoring and self- adjusting. This paper describes the need for next generation system software architectures, where components are agents, rather than objects masquerading as agents, and where support is provided for self-* properties (both existing self-chop and emerging self-* properties). These are discussed as exhibited in NASA missions, and in particular with reference to a NASA concept mission, ANTS, which is illustrative of future NASA exploration missions based on the technology of intelligent swarms.
NASA is researching advanced technologies for future exploration missions using intelligent swarms of robotic vehicles. One of these missions is the Autonomous Nan0 Technology Swarm (ANTS) mission that will explore the asteroid belt using 1,000 cooperative autonomous spacecraft. The emergent properties of intelligent swarms make it a potentially powerful concept, but at the same time more difficult to design and ensure that the proper behaviors will emerge. NASA is investigating formal methods and techniques for verification of such missions. The advantage of using formal methods is the ability to mathematically verify the behavior of a swarm, emergent or otherwise. Using the ANTS mission as a case study, we have evaluated multiple formal methods to determine their effectiveness in modeling and ensuring desired swarm behavior. This paper discusses the results of this evaluation and proposes an integrated formal method for ensuring correct behavior of future NASA intelligent swarms.
More than a decade ago, in "Ten Commandments of Formal Methods," we offered practical guidelines for projects that sought to use formal methods. Over the years, the article, which was based on our knowledge of successful industrial projects, has been widely cited and has generated much positive feedback. However, despite this apparent enthusiasm, formal methods use has not greatly increased, and some of the same attitudes about the infeasibility of adopting them persist. Formal methodists believe that introducing greater rigor will improve the software development process and yield software with better structure, greater maintainability, and fewer errors.
We discuss two software engineering aspects in the development of complex swarm-based systems. NASA researchers have been investigating various possible concept missions that would greatly advance future space exploration capabilities. The concept mission that we have focused on exploits the principles of autonomic computing as well as being based on the use of intelligent swarms, whereby a (potentially large) number of similar spacecraft collaborate to achieve mission goals. The intent is that such systems not only can be sent to explore remote and harsh environments but also are endowed with greater degrees of protection and longevity to achieve mission goals.
The field of Software Product Lines (SPL) emphasizes building a core architecture for a family of software products from which concrete products can be derived rapidly. This helps to reduce time-to-market, costs, etc., and can result in improved software quality and safety. Current AOSE methodologies are concerned with developing a single Multiagent System. We propose an initial approach to developing the core architecture of a Multiagent Systems Product Line (MAS-PL), exemplifying our approach with reference to a concept NASA mission based on multiagent technology.
We present a learning-based method for model completion and adaptation, which is based on the combination of two approaches: 1) R2D2C, a technique for mechanically transforming system requirements via provably equivalent models to running code, and 2) automata learning-based model extrapolation. The intended impact of this new combination is to make model completion and adaptation accessible to experts of the field, like biologists or engineers. The principle is briefly illustrated by generating models of biological procedures concerning gene activities in the production of proteins, although the main application is going to concern autonomic systems for space exploration.
Greater understanding of biology in modem times has enabled significant breakthroughs in improving healthcare, quality of life, and eliminating many diseases and congenital illnesses. Simultaneously there is a move towards emulating nature and copying many of the wonders uncovered in biology, resulting in "biologically inspired" systems. Significant results have been reported in a wide range of areas, with systems inspired by nature enabling exploration, communication, and advances that were never dreamed possible just a few years ago. We warn, that as in many other fields of endeavor, we should be inspired by nature and biology, not engage in mimicry. We describe some results of biological inspiration that augur promise in terms of improving the safety and security of systems, and in developing self-managing systems, that we hope will ultimately lead to self-governing systems.
Autonomic Computing (AC), self-management based on high level guidance from humans, is increasingly gaining momentum as the way forward in designing reliable systems that hide complexity and conquer IT management costs. Effectively, AC may be viewed as Policy-Based Self-Management. The Model Driven Architecture (MDA) approach focuses on building models that can be transformed into code in an automatic manner. In this paper, we look at ways to implement Policy-Based Self-Management by means of models that can be converted to code using transformations that follow the MDA philosophy. We propose a set of UML-based models to specify autonomic and autonomous features along with the necessary procedures, based on modification and composition of models, to deploy a policy as an executing system.
Agent technology, along with autonomous and autonomic computing, has emerged as a major field in computing, and will greatly influence the future development of complex computer-based systems. The area of research is strongly influenced by the Autonomic Computing initiative as well as by developments in biologically-inspired computing, and involves interdisciplinary interaction from those involved in research in social intelligence, psychology, arts, biology, computer science, computer communications and philosophy. This volume includes revised versions of papers presented at the workshop. The workshop was structured so as to allow adequate time for discussion and interaction, to exchange ideas and reflect on the motivations, scientific grounds and practical consequences of the concepts presented. Many of the ideas are truly "radical", and so authors were given time to revise their papers to reflect further thoughts on the ideas presented, and to reflect feedback received at the workshop.