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NASA NTRS2001

Web-Based Distributed Simulation of Aeronautical Propulsion System

An application was developed to allow users to run and view the Numerical Propulsion System Simulation (NPSS) engine simulations from web browsers. Simulations were performed on multiple INFORMATION POWER GRID (IPG) test beds. The Common Object Request Broker Architecture (CORBA) was used for brokering data exchange among machines and IPG/Globus for job scheduling and remote process invocation. Web server scripting was performed by JavaServer Pages (JSP). This application has proven to be an effective and efficient way to couple heterogeneous distributed components.

Zheng, Desheng↗

NASA NTRS2004

A Survey of Collectives

Due to the increasing sophistication and miniaturization of computational components, complex, distributed systems of interacting agents are becoming ubiquitous. Such systems, where each agent aims to optimize its own performance, but where there is a well-defined set of system-level performance criteria, are called collectives. The fundamental problem in analyzing/designing such systems is in determining how the combined actions of self-interested agents leads to 'coordinated' behavior on a iarge scale. Examples of artificial systems which exhibit such behavior include packet routing across a data network, control of an array of communication satellites, coordination of multiple deployables, and dynamic job scheduling across a distributed computer grid. Examples of natural systems include ecosystems, economies, and the organelles within a living cell. No current scientific discipline provides a thorough understanding of the relation between the structure of collectives and how well they meet their overall performance criteria. Although still very young, research on collectives has resulted in successes both in understanding and designing such systems. It is eqected that as it matures and draws upon other disciplines related to collectives, this field will greatly expand the range of computationally addressable tasks. Moreover, in addition to drawing on them, such a fully developed field of collective intelligence may provide insight into already established scientific fields, such as mechanism design, economics, game theory, and population biology. This chapter provides a survey to the emerging science of collectives.

Tumer, Kagan↗

NASA NTRS2013

Adoption of Test Driven Development and Continuous Integration for the Development of the Trick Simulation Toolkit

This paper describes the adoption of a Test Driven Development approach and a Continuous Integration System in the development of the Trick Simulation Toolkit, a generic simulation development environment for creating high fidelity training and engineering simulations at the NASA/Johnson Space Center and many other NASA facilities. It describes what was learned and the significant benefits seen, such as fast, thorough, and clear test feedback every time code is checked-in to the code repository. It also describes a system that encourages development of code that is much more flexible, maintainable, and reliable. The Trick Simulation Toolkit development environment provides a common architecture for user-defined simulations. Trick builds executable simulations using user-supplied simulation-definition files (S_define) and user supplied "model code". For each Trick-based simulation, Trick automatically provides job scheduling, checkpoint / restore, data-recording, interactive variable manipulation (variable server), and an input-processor. Also included are tools for plotting recorded data and various other supporting tools and libraries. Trick is written in C/C++ and Java and supports both Linux and MacOSX. Prior to adopting this new development approach, Trick testing consisted primarily of running a few large simulations, with the hope that their complexity and scale would exercise most of Trick's code and expose any recently introduced bugs. Unsurprising, this approach yielded inconsistent results. It was obvious that a more systematic, thorough approach was required. After seeing examples of some Java-based projects that used the JUnit test framework, similar test frameworks for C and C++ were sought. Several were found, all clearly inspired by JUnit. Googletest, a freely available Open source testing framework, was selected as the most appropriate and capable. The new approach was implemented while rewriting the Trick memory management component, to eliminate a fundamental design flaw. The benefits became obvious almost immediately, not just in the correctness of the individual functions and classes but also in the correctness and flexibility being added to the overall design. Creating code to be testable, and testing as it was created resulted not only in better working code, but also in better-organized, flexible, and readable (i.e., articulate) code. This was, in essence the Test-driven development (TDD) methodology created by Kent Beck. Seeing the benefits of Test Driven Development, other Trick components were refactored to make them more testable and tests were designed and implemented for them.

Penn, John M.↗

NASA NTRS2016

The Trick Simulation Toolkit: A NASA/Opensource Framework for Running Time Based Physics Models

The Trick Simulation Toolkit is a simulation development environment used to create high fidelity training and engineering simulations at the NASA Johnson Space Center and many other NASA facilities. Its purpose is to generate a simulation executable from a collection of user-supplied models and a simulation definition file. For each Trick-based simulation, Trick automatically provides job scheduling, numerical integration, the ability to write and restore human readable checkpoints, data recording, interactive variable manipulation, a run-time interpreter, and many other commonly needed capabilities. This allows simulation developers to concentrate on their domain expertise and the algorithms and equations of their models. Also included in Trick are tools for plotting recorded data and various other supporting utilities and libraries. Trick is written in C/C++ and Java and supports both Linux and MacOSX computer operating systems. This paper describes Trick's design and use at NASA Johnson Space Center.

Penn, John M.↗

NASA NTRS1989

Focus of attention in an activity-based scheduler

Earlier research in job shop scheduling has demonstrated the advantages of opportunistically combining order-based and resource-based scheduling techniques. An even more flexible approach is investigated where each activity is considered a decision point by itself. Heuristics to opportunistically select the next decision point on which to focus attention (i.e., variable ordering heuristics) and the next decision to be tried at this point (i.e., value ordering heuristics) are described that probabilistically account for both activity precedence and resource requirement interactions. Preliminary experimental results indicate that the variable ordering heuristic greatly increases search efficiency. While least constraining value ordering heuristics have been advocated in the literature, the experimental results suggest that other value ordering heuristics combined with our variable-ordering heuristic can produce much better schedules without significantly increasing search.

Sadeh, Norman↗

NASA NTRS1987

Scheduling real-time, periodic jobs using imprecise results

A process is called a monotone process if the accuracy of its intermediate results is non-decreasing as more time is spent to obtain the result. The result produced by a monotone process upon its normal termination is the desired result; the error in this result is zero. External events such as timeouts or crashes may cause the process to terminate prematurely. If the intermediate result produced by the process upon its premature termination is saved and made available, the application may still find the result unusable and, hence, acceptable; such a result is said to be an imprecise one. The error in an imprecise result is nonzero. The problem of scheduling periodic jobs to meet deadlines on a system that provides the necessary programming language primitives and run-time support for processes to return imprecise results is discussed. This problem differs from the traditional scheduling problems since the scheduler may choose to terminate a task before it is completed, causing it to produce an acceptable but imprecise result. Consequently, the amounts of processor time assigned to tasks in a valid schedule can be less than the amounts of time required to complete the tasks. A meaningful formulation of this problem taking into account the quality of the overall result is discussed. Three algorithms for scheduling jobs for which the effects of errors in results produced in different periods are not cumulative are described, and their relative merits are evaluated.

Liu, Jane W. S.↗

NASA NTRS2014

Magnetospheric MultiScale (MMS) System Manager

The Magnetospheric MultiScale (MMS) mission is an ambitious NASA space science mission in which 4 spacecraft are flown in tight formation about a highly elliptical orbit. Each spacecraft has multiple instruments that measure particle and field compositions in the Earths magnetosphere. By controlling the members relative motion, MMS can distinguish temporal and spatial fluctuations in a way that a single spacecraft cannot.To achieve this control, 2 sets of four maneuvers, distributed evenly across the spacecraft must be performed approximately every 14 days. Performing a single maneuver on an individual spacecraft is usually labor intensive and the complexity becomes clearly increases with four. As a result, the MMS flight dynamics team turned to the System Manager to put the routine or error-prone under machine control freeing the analysts for activities that require human judgment.The System Manager is an expert system that is capable of handling operations activities associated with performing MMS maneuvers. As an expert system, it can work off a known schedule, launching jobs based on a one-time occurrence or on a set reoccurring schedule. It is also able to detect situational changes and use event-driven programming to change schedules, adapt activities, or call for help.

Ground System Expert Automation↗

NASA NTRS1972

What motivates researchers in times of economic uncertainty.

Results of a study initiated late in 1970 to obtain both a measure of on-and-around-the-job factors which were 'motivating' to engineers and scientists, and to obtain an indication of how the relative importance of these factors changes as a result of the uncertain economic environment. A questionnaire, 'The Jackman Job Satisfaction Schedule,' was used to satisfy the needs of the study. It is concluded that managers can enhance the feeling of motivation by making individual job assignments interesting and challenging, by formulating significant milestones and end points into job content, and by assigning ample rewards with corresponding responsibility. In times of economic uncertainty increased emphasis should be given to security-related aspects of employment.

Bucher, G. C.↗

NASA NTRSDate not supplied

Introducing Tropical Geometric Approaches to Delay Tolerant Networking Optimization

Delay Tolerant Networking (DTN) is the standard approach to the networking of space systems with the goal of supporting the Solar System Internet (SSI). Current space networks have a small scale and often depend on rigorously scheduled (pre-determined) contact opportunities; this manual approach inhibits scalability. The goal of this paper is to recast these scheduling problems in order to apply the optimization machinery of tropical geometry. Contact opportunities in space are dependent on such factors as orbital mechanics and asset availability, which induce time-varying connectivity; indeed, end-to-end connectivity might never occur. Routing optimization within this structure is classically difficult and typically utilizes Dijkstra's algorithm as applied to contact graphs. Alternatively, we follow the successes of tropical geometry in train schedule optimization, job assignments, and even traditional networking, by extending this approach to this more general (i.e. disconnected) problem space. These successes imply tropical geometry provides a useful framework in the context of DTNs, starting with applications to queuing theory and long-haul links. Recently, tropical geometry has been applied to parametric path optimization on graphs with variable edge weights. In this work, we extend these advances to account for the problem of routing in a space network, and find that tropical geometry is well-suited to the challenges offered by this new setting, including contact schedules featuring probabilities. Our approach leverages the combinatorial nature of the problem to give feasible shortest path trees in the presence of variable channel conditions and latency, evolving topologies, and uncertainty inherent in space routing. We discuss our tropical approach to DTN for two Python implementations, a Verilog Tropical ALU implementation, tropical frameworks for other parametric graph problems, and solution stability. Lastly, a program for future work is included to illuminate the path ahead.

Delay Tolerant Networking↗

NASA NTRS1977

Solar power satellite. System definition study. Part 1, volume 3: Construction, transportation and cost analyses

Concepts developed for both LEO and GEO construction of photovoltaic and thermal engine satellites are analyzed. Topics discussed include: satellite construction; crew scheduling; crew jobs and organizations; operator productivity rating; constructability rating; transportation systems for cargo launch, refueling operations, personnel transport, and orbit transfer; collision analysis, cost analysis, and radiation evironment and effects.

Source record↗

NASA NTRS1992

Constraint monitoring in TOSCA

The Job-Shop Scheduling Problem (JSSP) deals with the allocation of resources over time to factory operations. Allocations are subject to various constraints (e.g., production precedence relationships, factory capacity constraints, and limits on the allowable number of machine setups) which must be satisfied for a schedule to be valid. The identification of constraint violations and the monitoring of constraint threats plays a vital role in schedule generation in terms of the following: (1) directing the scheduling process; and (2) informing scheduling decisions. This paper describes a general mechanism for identifying constraint violations and monitoring threats to the satisfaction of constraints throughout schedule generation.

Beck, Howard↗

NASA NTRS1995

An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics

This report is a repository of the results obtained from a large scale empirical comparison of seven iterative and evolution-based optimization heuristics. Twenty-seven static optimization problems, spanning six sets of problem classes which are commonly explored in genetic algorithm literature, are examined. The problem sets include job-shop scheduling, traveling salesman, knapsack, binpacking, neural network weight optimization, and standard numerical optimization. The search spaces in these problems range from 2368 to 22040. The results indicate that using genetic algorithms for the optimization of static functions does not yield a benefit, in terms of the final answer obtained, over simpler optimization heuristics. Descriptions of the algorithms tested and the encodings of the problems are described in detail for reproducibility.

Baluja, Shumeet↗

NASA NTRS2001

Pricing the Computing Resources: Reading Between the Lines and Beyond

Distributed computing systems have the potential to increase the usefulness of existing facilities for computation without adding anything physical, but that is realized only when necessary administrative features are in place. In a distributed environment, the best match is sought between a computing job to be run and a computer to run the job (global scheduling), which is a function that has not been required by conventional systems. Viewing the computers as 'suppliers' and the users as 'consumers' of computing services, markets for computing services/resources have been examined as one of the most promising mechanisms for global scheduling. We first establish why economics can contribute to scheduling. We further define the criterion for a scheme to qualify as an application of economics. Many studies to date have claimed to have applied economics to scheduling. If their scheduling mechanisms do not utilize economics, contrary to their claims, their favorable results do not contribute to the assertion that markets provide the best framework for global scheduling. We examine the well-known scheduling schemes, which concern pricing and markets, using our criterion of what application of economics is. Our conclusion is that none of the schemes examined makes full use of economics.

Nakai, Junko↗

NASA NTRS2011

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

pattern recognition↗

NASA NTRS1989

Application of a hybrid generation/utility assessment heuristic to a class of scheduling problems

A two-stage heuristic solution approach for a class of multiobjective, n-job, 1-machine scheduling problems is described. Minimization of job-to-job interference for n jobs is sought. The first stage generates alternative schedule sequences by interchanging pairs of schedule elements. The set of alternative sequences can represent nodes of a decision tree; each node is reached via decision to interchange job elements. The second stage selects the parent node for the next generation of alternative sequences through automated paired comparison of objective performance for all current nodes. An application of the heuristic approach to communications satellite systems planning is presented.

Heyward, Ann O.↗

NASA NTRS1991

An expert system for planning and scheduling in a telerobotic environment

A knowledge based approach to assigning tasks to multi-agents working cooperatively in jobs that require a telerobot in the loop was developed. The generality of the approach allows for such a concept to be applied in a nonteleoperational domain. The planning architecture known as the task oriented planner (TOP) uses the principle of flow mechanism and the concept of planning by deliberation to preserve and use knowledge about a particular task. The TOP is an open ended architecture developed with a NEXPERT expert system shell and its knowledge organization allows for indirect consultation at various levels of task abstraction. Considering that a telerobot operates in a hostile and nonstructured environment, task scheduling should respond to environmental changes. A general heuristic was developed for scheduling jobs with the TOP system. The technique is not to optimize a given scheduling criterion as in classical job and/or flow shop problems. For a teleoperation job schedule, criteria are situation dependent. A criterion selection is fuzzily embedded in the task-skill matrix computation. However, goal achievement with minimum expected risk to the human operator is emphasized.

Ntuen, Celestine A.↗

NASA NTRS1994

Scheduling with genetic algorithms

In many domains, scheduling a sequence of jobs is an important function contributing to the overall efficiency of the operation. At Boeing, we develop schedules for many different domains, including assembly of military and commercial aircraft, weapons systems, and space vehicles. Boeing is under contract to develop scheduling systems for the Space Station Payload Planning System (PPS) and Payload Operations and Integration Center (POIC). These applications require that we respect certain sequencing restrictions among the jobs to be scheduled while at the same time assigning resources to the jobs. We call this general problem scheduling and resource allocation. Genetic algorithms (GA's) offer a search method that uses a population of solutions and benefits from intrinsic parallelism to search the problem space rapidly, producing near-optimal solutions. Good intermediate solutions are probabalistically recombined to produce better offspring (based upon some application specific measure of solution fitness, e.g., minimum flowtime, or schedule completeness). Also, at any point in the search, any intermediate solution can be accepted as a final solution; allowing the search to proceed longer usually produces a better solution while terminating the search at virtually any time may yield an acceptable solution. Many processes are constrained by restrictions of sequence among the individual jobs. For a specific job, other jobs must be completed beforehand. While there are obviously many other constraints on processes, it is these on which we focussed for this research: how to allocate crews to jobs while satisfying job precedence requirements and personnel, and tooling and fixture (or, more generally, resource) requirements.

Fennel, Theron R.↗

NASA NTRS1992

The MICRO-BOSS scheduling system: Current status and future efforts

In this paper, a micro-opportunistic approach to factory scheduling was described that closely monitors the evolution of bottlenecks during the construction of the schedule and continuously redirects search towards the bottleneck that appears to be most critical. This approach differs from earlier opportunistic approaches, as it does not require scheduling large resource subproblems or large job subproblems before revising the current scheduling strategy. This micro-opportunistic approach was implemented in the context of the MICRO-BOSS factory scheduling system. A study comparing MICRO-BOSS against a macro-opportunistic scheduler suggests that the additional flexibility of the micro-opportunistic approach to scheduling generally yields important reductions in both tardiness and inventory. Current research efforts include: adaptation of MICRO-BOSS to deal with sequence-dependent setups and development of micro-opportunistic reactive scheduling techniques that will enable the system to patch the schedule in the presence of contingencies such as machine breakdowns, raw materials arriving late, job cancellations, etc.

Sadeh, Norman M.↗