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At least 91 records · Page 5

An overview of the artificial intelligence and expert systems component of RICIS

Artificial Intelligence and Expert Systems are the important component of RICIS (Research Institute and Information Systems) research program. For space applications, a number of problem areas that should be able to make good use of the above tools include: resource allocation and management, control and monitoring, environmental control and life support, power distribution, communications scheduling, orbit and attitude maintenance, redundancy management, intelligent man-machine interfaces and fault detection, isolation and recovery.

Feagin, Terry↗

Performance and policy dimensions in internet routing

The Internet Routing Project, referred to in this report as the 'Highball Project', has been investigating architectures suitable for networks spanning large geographic areas and capable of very high data rates. The Highball network architecture is based on a high speed crossbar switch and an adaptive, distributed, TDMA scheduling algorithm. The scheduling algorithm controls the instantaneous configuration and swell time of the switch, one of which is attached to each node. In order to send a single burst or a multi-burst packet, a reservation request is sent to all nodes. The scheduling algorithm then configures the switches immediately prior to the arrival of each burst, so it can be relayed immediately without requiring local storage. Reservations and housekeeping information are sent using a special broadcast-spanning-tree schedule. Progress to date in the Highball Project includes the design and testing of a suite of scheduling algorithms, construction of software reservation/scheduling simulators, and construction of a strawman hardware and software implementation. A prototype switch controller and timestamp generator have been completed and are in test. Detailed documentation on the algorithms, protocols and experiments conducted are given in various reports and papers published. Abstracts of this literature are included in the bibliography at the end of this report, which serves as an extended executive summary.

Mills, David L.↗

Cost efficient command management

The design and implementation of a command management system (CMS) for a NASA control center, is described. The technology innovations implemented in the CMS provide the infrastructure required for operations cost reduction and future development cost reduction through increased operational efficiency and reuse in future missions. The command management design facilitates error-free operations which enables the automation of the routine control center functions and allows for the distribution of scheduling responsibility to the instrument teams. The reusable system was developed using object oriented methodologies.

Brandt, Theresa↗

GPS Navigation for the Magnetospheric Multi-Scale Mission

In 2014. NASA is scheduled to launch the Magnetospheric Multiscale Mission (MMS), a four-satellite formation designed to monitor fluctuations in the Earth's magnetosphere. This mission has two planned phases with different orbits (1? x 12Re and 1.2 x 25Re) to allow for varying science regions of interest. To minimize ground resources and to mitigate the probability of collisions between formation members, an on-board orbit determination system consisting of a Global Positioning System (GPS) receiver and crosslink transceiver was desired. Candidate sensors would be required to acquire GPS signals both below and above the constellation while spinning at three revolutions-per-minute (RPM) and exchanging state and science information among the constellation. The Intersatellite Ranging and Alarm System (IRAS), developed by Goddard Space Flight Center (GSFC) was selected to meet this challenge. IRAS leverages the eight years of development GSFC has invested in the Navigator GPS receiver and its spacecraft communication expertise, culminating in a sensor capable of absolute and relative navigation as well as intersatellite communication. The Navigator is a state-of-the-art receiver designed to acquire and track weak GPS signals down to -147dBm. This innovation allows the receiver to track both the main lobe and the much weaker side lobe signals. The Navigator's four antenna inputs and 24 tracking channels, together with customized hardware and software, allow it to seamlessly maintain visibility while rotating. Additionally, an extended Kalman filter provides autonomous, near real-time, absolute state and time estimates. The Navigator made its maiden voyage on the Space Shuttle during the Hubble Servicing Mission, and is scheduled to fly on MMS as well as the Global Precipitation Measurement Mission (GPM). Additionally, Navigator's acquisition engine will be featured in the receiver being developed for the Orion vehicle. The crosslink transceiver is a 1/4 Watt transmitter utilizing a TDMA schedule to distribute a science quality message to all constellation members every ten seconds. Additionally the system generates one-way range measurements between formation members which is used as input to the Kalman filter. In preparation for the MMS Preliminary Design Review (PDR), the Navigator was required to pass a series of Technology Readiness Level (TRL) tests to earn the necessary TRL-6 classification. The TRL-6 level is achieved by demonstrating a prototype unit in a relevant end-to-end environment. The IRAS unit was able to meet all requirements during the testing phase, and has thus been TRL-6 qualified

Bamford, William↗

Mission Activity Planning for Humans and Robots on the Moon

A series of studies is conducted to develop a systematic approach to optimizing, both in terms of the distribution and scheduling of tasks, scenarios in which astronauts and robots accomplish a group of activities on the Moon, given an objective function (OF) and specific resources and constraints. An automated planning tool is developed as a key element of this optimization system.

task allocation↗

A Novel LDPP-MADDPG Approach for Distributed Power Allocation in mmWave Cellular Networks

This paper considers the problem of distributed beam scheduling and power allocation problem in millimeter- Wave (mmWave) cellular networks, in which multiple Base Stations (BSs) operate as individual operators over a shared spectrum. We propose a novel learning-aided approach that integrates the Lyapunov Drift-Plus-Penalty (LDPP) framework and Multi-agent Deep Deterministic Policy Gradient (MADDPG) reinforcement learning algorithms. This offers a powerful approach to learning stable and constraint-aware policies, reaping the joint benefit of both LDPP and MADDPG, in complex multiagent environments. The major challenge for this approach is to integrate these two approaches in a meaningful and effective manner. The key idea to solve this problem is to introduce a novel feature of local observation that incorporates potential negative value of the reward function due to the stochastic constraints introduced by the LDPP framework. Empirical results demonstrate that our proposed scheme outperforms the baseline methods under various conditions.

99 - GENERAL AND MISCELLANEOUS↗

Distribution of a Generic Mission Planning and Scheduling Toolkit for Astronomical Spacecraft

This 2-year report describes the progress made to date on the project to package and distribute the planning and scheduling toolkit for the SWAS astronomical spacecraft. SWAS was scheduled to be launched on a Pegasus XL vehicle in fall 1995. Three separate failures in the launch vehicle have delayed the SWAS launch. The researchers have used this time to continue developing scheduling algorithms and GUI design. SWAS is expected to be launched this year.

Kleiner, Steven C.↗

Application of future remote sensing systems to irrigation

Area estimates of irrigated crops and knowledge of crop type are required for modeling water consumption to assist farmers, rangers, and agricultural consultants in scheduling irrigation for distributed management of crop yields. Information on canopy physiology and soil moisture status on a spatial basis is potentially available from remote sensors, so the questions to be addressed relate to: (1) timing (data frequency, instantaneous and integrated measurement); and scheduling (widely distributed spatial demands); (2) spatial resolution; (3) radiometric and geometric accuracy and geoencoding; and (4) information/data distribution. This latter should be overnight, with no central storage, onsite capture, and low cost.

Miller, L. D.↗

Adaptive PID Gain Scheduling Control for Hydropower Turbine Using Neural CDE and Stochastic Distribution Shaping

This paper introduces a gain-scheduling PID controller design strategy for hydroturbine frequency control mode. This scheme first uses real data to learn the nonlinear dynamics of the hydroturbine using neural controlled differential equations and then perturbs the obtained nonlinear system at different equilibrium points, based on which a static output feedback adaptive dynamic programming algorithm is then used to optimize the PID gains for each equilibrium point. Moreover, a continuous-time version of stochastic distribution control is proposed to further fine-tune the optimized PID gains. Finally, the controller is obtained by implementing linear interpolation between the optimized PID control gains. The simulation results show that the proposed gain-scheduling PID controller can control a larger range of operation points compared with the given fixed PID controller and the baseline method. Compared with the given fixed PID controller, the proposed gain-scheduling PID controller can regulate hydroturbine frequency against disturbances induced by power-load variation with over 50% less overshoot for some operation points.

13 HYDRO ENERGY↗

Optimal Energy Storage Schedules for Load Leveling and Ramp Rate Control in Distribution Systems

Continued integration of distributed energy resources (DERs) into the grid, such as solar PVs, at a large-scale, contributes into the famous Duck Curve. New DER management algorithms are therefore deemed necessary to alleviate rapid variations within net load profiles of distribution systems. Herein this paper proposes a process to determine the optimal energy storage schedules for leveling the distribution circuit feederhead net load. A series of sensitivity analyses shows how the proposed method can be used to determine the optimal energy storage schedules with different capacities, state of charge requirements, and net load ramp rate limitations.

25 ENERGY STORAGE↗

Population-based learning of load balancing policies for a distributed computer system

Effective load-balancing policies use dynamic resource information to schedule tasks in a distributed computer system. We present a novel method for automatically learning such policies. At each site in our system, we use a comparator neural network to predict the relative speedup of an incoming task using only the resource-utilization patterns obtained prior to the task's arrival. Outputs of these comparator networks are broadcast periodically over the distributed system, and the resource schedulers at each site use these values to determine the best site for executing an incoming task. The delays incurred in propagating workload information and tasks from one site to another, as well as the dynamic and unpredictable nature of workloads in multiprogrammed multiprocessors, may cause the workload pattern at the time of execution to differ from patterns prevailing at the times of load-index computation and decision making. Our load-balancing policy accommodates this uncertainty by using certain tunable parameters. We present a population-based machine-learning algorithm that adjusts these parameters in order to achieve high average speedups with respect to local execution. Our results show that our load-balancing policy, when combined with the comparator neural network for workload characterization, is effective in exploiting idle resources in a distributed computer system.

Mehra, Pankaj↗

The Consolidated Planning and Scheduling System for Space Transportation and Space Station operations - Successful development experience

In 1992, NASA made the decision to evolve a Consolidated Planning System (CPS) by adding the Space Transportation System (STS) requirements to the Space Station Freedom (SSF) planning software. This paper describes this evolutionary process, which began with a series of six-month design-build-test cycles, using a domain-independent architecture and a set of developmental tools known as the Advanced Scheduling Environment. It is shown that, during these tests, the CPS could be used at multiple organizational levels of planning and for integrating schedules from geographically distributed (including international) planning environments. The potential for using the CPS for other planning and scheduling tasks in the SSF program is being currently examined.

Hornstein, Rhoda S.↗

Constraint based scheduling for the Goddard Space Flight Center distributed Active Archive Center's data archive and distribution system

The Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) has been operational since October 1, 1993. Its mission is to support the Earth Observing System (EOS) by providing rapid access to EOS data and analysis products, and to test Earth Observing System Data and Information System (EOSDIS) design concepts. One of the challenges is to ensure quick and easy retrieval of any data archived within the DAAC's Data Archive and Distributed System (DADS). Over the 15-year life of EOS project, an estimated several Petabytes (10(exp 15)) of data will be permanently stored. Accessing that amount of information is a formidable task that will require innovative approaches. As a precursor of the full EOS system, the GSFC DAAC with a few Terabits of storage, has implemented a prototype of a constraint-based task and resource scheduler to improve the performance of the DADS. This Honeywell Task and Resource Scheduler (HTRS), developed by Honeywell Technology Center in cooperation the Information Science and Technology Branch/935, the Code X Operations Technology Program, and the GSFC DAAC, makes better use of limited resources, prevents backlog of data, provides information about resources bottlenecks and performance characteristics. The prototype which is developed concurrently with the GSFC Version 0 (V0) DADS, models DADS activities such as ingestion and distribution with priority, precedence, resource requirements (disk and network bandwidth) and temporal constraints. HTRS supports schedule updates, insertions, and retrieval of task information via an Application Program Interface (API). The prototype has demonstrated with a few examples, the substantial advantages of using HTRS over scheduling algorithms such as a First In First Out (FIFO) queue. The kernel scheduling engine for HTRS, called Kronos, has been successfully applied to several other domains such as space shuttle mission scheduling, demand flow manufacturing, and avionics communications scheduling.

Short, Nick, Jr.↗

Distribution of a Generic Mission Planning and Scheduling Toolkit for Astronomical Spacecraft

Work is progressing as outlined in the proposal for this contract. A working planning and scheduling system has been documented and packaged and made available to the WIRE Small Explorer group at JPL, the FUSE group at JHU, the NASA/GSFC Laboratory for Astronomy and Solar Physics and the Advanced Planning and Scheduling Branch at STScI. The package is running successfully on the WIRE computer system. It is expected that the WIRE will reuse significant portions of the SWAS code in its system. This scheduling system itself was tested successfully against the spacecraft hardware in December 1995. A fully automatic scheduling module has been developed and is being added to the toolkit. In order to maximize reuse, the code is being reorganized during the current build into object-oriented class libraries. A paper describing the toolkit has been written and is included in the software distribution. We have experienced interference between the export and production versions of the toolkit. We will be requesting permission to reprogram funds in order to purchase a standalone PC onto which to offload the export version.

Kleiner, Steven C.↗

Joint scheduling of energy, fast and primary frequency response reserves in integrated transmission–distribution networks

Inverter-based distributed energy resources (DERs) connected to distribution networks (DNs) can provide fast frequency support, but their reserve deliverability depends on feeder constraints and differs from synchronous primary frequency response (PFR). Existing transmission–distribution coordination studies usually treat reserve generically or neglect feeder-level feasibility, while frequency-security scheduling studies rarely represent distribution feeders explicitly. This paper develops a bi-level day-ahead scheduling framework for integrated transmission–distribution networks that jointly clears energy, transmission-side PFR, and distribution-side fast frequency response (FFR) under exogenous hourly inertia and largest-loss inputs from an external unit commitment (UC) schedule. The transmission problem is modeled with DC-optimal power flow (OPF) and closed-form second-order cone (SOC) frequency-security constraints, whereas each DN is represented by a reserve-aware branch-flow AC-OPF so that scheduled fast reserves remain deliverable during activation. The bi-level problem is reformulated through Karush–Kuhn–Tucker (KKT) conditions into a mixed-integer SOC program, and a penalty term is used to tighten the distribution-network relaxation. In the reduced test system, lower exogenous inertia increased the required primary response from 179.64 MW to 191.08 MW, distribution-side fast response reduced total frequency-response procurement by up to 4.9%, and neglecting distribution constraints overstated the combined distribution-side energy and reserve award by up to 18%. In the expanded study, the largest case was solved in 2.02 s with a 0.00% optimality gap. Time-domain simulations kept the frequency nadir above 59.0 Hz in all tested hours. These results demonstrate the value of fast-response modeling and distribution-feasible reserve delivery in coordinated market clearing.

Noh, Seung-Gil↗

Integrated planning and scheduling for Earth science data processing

Several current NASA programs such as the EOSDIS Core System (ECS) have data processing and data management requirements that call for an integrated planning and scheduling capability. In this paper, we describe the experience of applying advanced scheduling technology operationally, in terms of what was accomplished, lessons learned, and what remains to be done in order to achieve similar successes in ECS and other programs. We discuss the importance and benefits of advanced scheduling tools, and our progress toward realizing them, through examples and illustrations based on ECS requirements. The first part of the paper focuses on the Data Archive and Distribution (DADS) V0 Scheduler. We then discuss system integration issues ranging from communication with the scheduler to the monitoring of system events and re-scheduling in response to them. The challenge of adapting the scheduler to domain-specific features and scheduling policies is also considered. Extrapolation to the ECS domain raises issues of integrating scheduling with a product-generation planner (such as PlaSTiC), and implementing conditional planning in an operational system. We conclude by briefly noting ongoing technology development and deployment projects being undertaken by HTC and the ISTB.

Boddy, Mark↗

Planning Systems for Distributed Operations

This viewgraph representation presents an overview of the mission planning process involving distributed operations (such as the International Space Station (ISS)) and the computer hardware and software systems needed to support such an effort. Topics considered include: evolution of distributed planning systems, ISS distributed planning, the Payload Planning System (PPS), future developments in distributed planning systems, Request Oriented Scheduling Engine (ROSE) and Next Generation distributed planning systems.

Maxwell, Theresa G.↗

Scalable Circuit Cutting and Scheduling in a Resource-constrained and Distributed Quantum System

Despite quantum computing's rapid development, current systems remain limited in practical applications due to their limited qubit count and quality. Various technologies, such as superconducting, trapped ions, and neutral atom quantum computing technologies are progressing towards a fault tolerant era, however they all face a diverse set of challenges in scalability and control. Recent efforts have focused on multi-node quantum systems that connect multiple smaller quantum devices to execute larger circuits. Future demonstrations hope to use quantum channels to couple systems, however current demonstrations can leverage classical communication with circuit cutting techniques. This involves cutting large circuits into smaller subcircuits and reconstructing them post-execution. However, existing cutting methods are hindered by lengthy search times as the number of qubits and gates increases. Additionally, they often fail to effectively utilize the resources of various worker configurations in a multi-node system. To address these challenges, we introduce FitCut, a novel approach that transforms quantum circuits into weighted graphs and utilizes a community-based, bottom-up approach to cut circuits according to resource constraints, e.g., qubit counts, on each worker. FitCut also includes a scheduling algorithm that optimizes resource utilization across workers. Implemented with Qiskit and evaluated extensively, FitCut significantly outperforms the Qiskit Circuit Knitting Toolbox, reducing time costs by factors ranging from 3 to 2000 and improving resource utilization rates by up to 3.88 times on the worker side, achieving a system-wide improvement of 2.86 times.

Kan, Shuwen [Fordham University]↗