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Program provides batch and device queueing facilities for various computers networked in UNIX environment. Allows network manager to allocate and track resources across network without requiring user to specifically log in on remote target machines.
Plans for the development of an international Space Station complex in cooperation with Japan, Canada, and the European Space Agency are reviewed. The discussion covers the planned uses of the Space Station, the principal research facilities, allocation of the resources available to the research facilities, and tactical and strategic planning related to the Space Station project. Particular attention is given to problems related to microgravity sciences and approaches to the solutions of these problems.
Job scheduling is a deceptively complex subfield of computer science. The highly combinatorial nature of the problem, which is NP-complete in nearly all cases, requires a scheduling program to intelligently transverse an immense search tree to create the best possible schedule in a minimal amount of time. In addition, the program must continually make adjustments to the initial schedule when faced with last-minute user requests, cancellations, unexpected device failures, quests, cancellations, unexpected device failures, etc. A good scheduler must be quick, flexible, and efficient, even at the expense of generating slightly less-than-optimal schedules. The Space Communication Scheduler (SCS) is an intelligent rule-based scheduling system. SCS is an adaptive deadline scheduler which allocates modular communications resources to meet an ordered set of user-specified job requests on board the NASA Space Station. SCS uses pattern matching techniques to detect potential conflicts through algorithmic and heuristic means. As a result, the system generates and maintains high density schedules without relying heavily on backtracking or blind search techniques. SCS is suitable for many common real-world applications.
Two issues are addressed which arise in the task of detecting anomalous behavior in complex systems with numerous sensor channels: how to adjust alarm thresholds dynamically, within the changing operating context of the system, and how to utilize sensors selectively, so that nominal operation can be verified reliably without processing a prohibitive amount of sensor data. The approach involves simulation of a causal model of the system, which provides information on expected sensor values, and on dependencies between predicted events, useful in assessing the relative importance of events so that sensor resources can be allocated effectively. The potential applicability of this work to the execution monitoring of robot task plans is briefly discussed.
Results of a life science impact analysis for accommodation to the Space Station of a manned Mars mission are discussed. In addition to addressing such issues as on-orbit vehicle assembly and checkout, the study also assessed the impact of a life science research program on the station. A better understanding of the effects on the crew of long duration exposure to the hostile space environment and to develop controls for adverse effects was the objective. Elements and products of the life science accommodation include: the identification of critical research areas; the outline of a research program consistent with the mission timeframe; the quantification of resource requirements; the allocation of functions to station facilities; and a determination of the impact on the Space Station program and of the baseline configuration. Results indicate the need at the Space Station for two dedicated life science lab modules; a pocket lab to support a 4-meter centrifuge; a quarantine module for the Mars Sample Return Mission; 3.9 man-years of average crew time; and 20 kilowatts of electrical power.
The European Space Agency is developing, in the context of the ARTEMIS program, a multibeam reconfigurable mobile payload to provide pre-operational land-mobile satellite services at the L-band over Europe. The L-band Land-Mobile (LLM) payload features high capacity at L-band, efficient use of the L-band spectrum resources, and flexibility in reconfiguring the allocation of bandwith and RF power resources to the different beams. Additionally, a number of features were added to the payload purely for experimental purposes, like the provision of one steerable spot beam which can be repositioned anywhere within the coverage area, and the possibility to reuse L-band frequencies by spatial discrimination between non-adjacent beams, or via orthogonal polarizations. The architecture of the payload and the hardware implementation of the most critical subsystems are described.
This paper considers a decomposition approach for optimization of the reliability of a large system with a general network structure. A 3-level methodology is developed for optimal allocation of available resources among subsystems in order to ensure maximization of system-reliability. The decentralized nature of this methodology greatly reduces the complexity of the large problem and facilitates seeking the optimal solution. Two examples show that the complexity of a large system can be greatly reduced by solving several smaller-dimensional sub-problems iteratively. Sub-problems whose dimensions are small can be efficiently solved by any existing nonlinear programming method. Another important feature of this approach is the possible simplification of the objective function during the solution. This leads in some cases to an analytic solution for the lower-level optimization problems in a 3-level decomposition solution.
The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of Space Shuttle mission planning.
The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of space shuttle mission planning.
Mechanical Engineering Senior Design Project 1 (ME4182) is a part of the NASA/University Advanced Design Program. Under this program, NASA allocates money and resources to students to be used in design work for a specified topic. The current topic is the exploration and colonization of Mars. The specific area in which we are to work is the transportation of the modules in which astronauts will live while on Mars. NASA is concerned about the weight of the module transferring system, as the shipping cost to Mars is quite expensive. NASA has specified that the weight of the system is to be minimized in order to reduce the shipping costs.
The Materials Science Research Rack I (MSRR-1) of the Materials Science Research Facility (MSRF) is a modular facility designed to accommodate two Experiment Modules (EM) simultaneously on board the International Space Station (ISS). One of these EMs will be the NASA/ESA EM being, developed collaboratively by NASA and the European Space Agency. The other EM position will be occupied by various multi-user EMs that will be exchanged in-orbit to accommodate a variety of materials science investigations. This paper discusses the resources, services, and allocations available to the EMs and briefly describes performance capabilities of the EMs currently planned for flight.
We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.
The TIES method is a forecasting environment whereby the decision-maker has the ability to easily assess and trade-off the impact of various technologies without sophisticated and time-consuming mathematical formulations. TIES provides a methodical approach where technically feasible alternatives can be identified with accuracy and speed to reduce design cycle time, and subsequently, life cycle costs, and was achieved through the use of various probabilistic methods, such as Response Surface Methodology and Monte Carlo Simulations. Furthermore, structured and systematic techniques are utilized from other fields to identify possible concepts and evaluation criteria by which comparisons can be made. This objective is achieved by employing the use of Morphological Matrices and Multi-Attribute Decision Making techniques. Through the execution of each step, a family of design alternatives for a given set of customer requirements can be identified and assessed subjectively or objectively. This methodology allows for more information (knowledge) to be brought into the earlier phases of the design process and will have direct implications on the affordability of the system. The increased knowledge allows for optimum allocation of company resources and quantitative justification for program decisions. Finally, the TIES method provided novel results and quantitative justification to facilitate decision making in the early stages of design so as to produce affordable and quality products.
Future science missions will require the use of multiple spacecraft with multiple sensor nodes autonomously responding and adapting to a dynamically changing space environment. The acquisition of random scientific events will require rapidly changing network topologies, distributed processing power, and a dynamic resource management strategy. Optimum utilization and configuration of spacecraft communications and navigation resources will be critical in meeting the demand of these stringent mission requirements. There are two important trends to follow with respect to NASA's (National Aeronautics and Space Administration) future scientific missions: the use of multiple satellite systems and the development of an integrated space communications network. Reconfigurable computing and communication systems may enable versatile adaptation of a spacecraft system's resources by dynamic allocation of the processor hardware to perform new operations or to maintain functionality due to malfunctions or hardware faults. Advancements in FPGA (Field Programmable Gate Array) technology make it possible to incorporate major communication and network functionalities in FPGA chips and provide the basis for a dynamically reconfigurable communication system. Advantages of higher computation speeds and accuracy are envisioned with tremendous hardware flexibility to ensure maximum survivability of future science mission spacecraft. This paper discusses the requirements, enabling technologies, and challenges associated with dynamically reconfigurable space communications systems.
Since the mid-1990's, the stated strategy of the Mars Exploration Program has been to Follow the Water. Although this strategy has been widely publicized, its degree of influence -- and the logic behind its current implementation (as reflected in mission planning, platform and instrument selection, and allocation of spacecraft resources) remains unclear. In response to this concern, we propose an integrated strategy for the post-2009 exploration of Mars that identifies the scientific objectives, rationale, sequence of missions, and specific investigations, that we believe provides the maximum possible science return by pursuing the most direct, cost-effective, and technically capable approach to following the water. This strategy is based on the orbital identification, high-resolution surface investigation, and ultimate sampling of the highest priority targets: near-surface liquid water and massive ground ice (potentially associated with the discharge of the outlflow channels or the relic of a former ocean). The analysis of such samples, in conjunction with the data acquired by the necessary precursor investigations (to identify the locations and characterize the environments of the optimum sampling sites), is expected to address a majority of the goals and high priority science objectives identified by MEPAG.
This paper introduces a dynamic metric that is based on the estimated ability of a program to withstand the effects of injected "semantic mutants" during execution by computing the same function as if the semantic mutants had not been injected. Semantic mutants include: (1) syntactic mutants injected into an executing program and (2) randomly selected values injected into an executing program's internal states. The metric is a function of a program, the method used for injecting these two types of mutants, and the program's input distribution; this metric is found through dynamic executions of the program. A program's ability to withstand the effects of injected semantic mutants by computing the same function when executed is then used as a tool for predicting the difficulty that will be incurred during random testing to reveal the existence of faults, i.e., the metric suggests the likelihood that a program will expose the existence of faults during random testing assuming faults were to exist. If the metric is applied to a module rather than to a program, the metric can be used to guide the allocation of testing resources among a program's modules. In this manner the metric acts as a white-box testing tool for determining where to concentrate testing resources. Index Terms: Revealing ability, random testing, input distribution, program, fault, failure.
Over the past several years, we have focused on developing fault models for space mission software. In general, these models use measurable attributes of a software system and its development process to estimate the number of faults inserted into the system during its development; their outputs can be used to better estimate the resources to be allocated to fault identification and removal for all system components.
Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it.