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At least 19 records

Performance Monitoring of Distributed Data Processing Systems

Test and checkout systems are essential components in ensuring safety and reliability of aircraft and related systems for space missions. A variety of systems, developed over several years, are in use at the NASA/KSC. Many of these systems are configured as distributed data processing systems with the functionality spread over several multiprocessor nodes interconnected through networks. To be cost-effective, a system should take the least amount of resource and perform a given testing task in the least amount of time. There are two aspects of performance evaluation: monitoring and benchmarking. While monitoring is valuable to system administrators in operating and maintaining, benchmarking is important in designing and upgrading computer-based systems. These two aspects of performance evaluation are the foci of this project. This paper first discusses various issues related to software, hardware, and hybrid performance monitoring as applicable to distributed systems, and specifically to the TCMS (Test Control and Monitoring System). Next, a comparison of several probing instructions are made to show that the hybrid monitoring technique developed by the NIST (National Institutes for Standards and Technology) is the least intrusive and takes only one-fourth of the time taken by software monitoring probes. In the rest of the paper, issues related to benchmarking a distributed system have been discussed and finally a prescription for developing a micro-benchmark for the TCMS has been provided.

Ojha, Anand K.↗

Extending the LWS Data Environment: Distributed Data Processing and Analysis

The final stages of this work saw changes to the original framework, as well as the completion and integration of several data processing services. Initially, it was thought that a peer-to-peer architecture was necessary to make this work possible. The peer-to-peer architecture provided many benefits including the dynamic discovery of new services that would be continually added. A prototype example was built and while it showed promise, a major disadvantage was seen in that it was not easily integrated into the existing data environment. While the peer-to-peer system worked well for finding and accessing distributed data processing services, it was found that its use was limited by the difficulty in calling it from existing tools and services. After collaborations with members of the data community, it was determined that our data processing system was of high value and that a new interface should be pursued in order for the community to take full advantage of it. As such; the framework was modified from a peer-to-peer architecture to a more traditional web service approach. Following this change multiple data processing services were added. These services include such things as coordinate transformations and sub setting of data. Observatory (VHO), assisted with integrating the new architecture into the VHO. This allows anyone using the VHO to search for data, to then pass that data through our processing services prior to downloading it. As a second attempt at demonstrating the new system, a collaboration was established with the Collaborative Sun Earth Connector (CoSEC) group at Lockheed Martin. This group is working on a graphical user interface to the Virtual Observatories and data processing software. The intent is to provide a high-level easy-to-use graphical interface that will allow access to the existing Virtual Observatories and data processing services from one convenient application. Working with the CoSEC group we provided access to our data processing tools from within their software. This now allows the CoSEC community to take advantage of our services and also demonstrates another means of accessing our system.

Narock, Thomas↗

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark and Hadoop manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape.

Hou, Shiyue↗

Air data measurement using distributed processing and fiber optics data transmission

Distributed processing, fiber optics technology, and redundancy management in the aircraft environment are discussed. The project features the development of an angle-of-attack and sideslip data collection system hich features: (1) two independent microprocessor controlled data collection and calibration units; (2) transmission of data to the control system on a fiber optic data bus; and (3) software implemented error detection and recovery.

Farry, K. A.↗

AVIRIS and TIMS data processing and distribution at the land processes distributed active archive center

The U.S. Government has initiated the Global Change Research program, a systematic study of the Earth as a complete system. NASA's contribution of the Global Change Research Program is the Earth Observing System (EOS), a series of orbital sensor platforms and an associated data processing and distribution system. The EOS Data and Information System (EOSDIS) is the archiving, production, and distribution system for data collected by the EOS space segment and uses a multilayer architecture for processing, archiving, and distributing EOS data. The first layer consists of the spacecraft ground stations and processing facilities that receive the raw data from the orbiting platforms and then separate the data by individual sensors. The second layer consists of Distributed Active Archive Centers (DAAC) that process, distribute, and archive the sensor data. The third layer consists of a user science processing network. The EOSDIS is being developed in a phased implementation. The initial phase, Version 0, is a prototype of the operational system. Version 0 activities are based upon existing systems and are designed to provide an EOSDIS-like capability for information management and distribution. An important science support task is the creation of simulated data sets for EOS instruments from precursor aircraft or satellite data. The Land Processes DAAC, at the EROS Data Center (EDC), is responsible for archiving and processing EOS precursor data from airborne instruments such as the Thermal Infrared Multispectral Scanner (TIMS), the Thematic Mapper Simulator (TMS), and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). AVIRIS, TIMS, and TMS are flown by the NASA-Ames Research Center ARC) on an ER-2. The ER-2 flies at 65000 feet and can carry up to three sensors simultaneously. Most jointly collected data sets are somewhat boresighted and roughly registered. The instrument data are being used to construct data sets that simulate the spectral and spatial characteristics of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument scheduled to be flown on the first EOS-AM spacecraft. The ASTER is designed to acquire 14 channels of land science data in the visible and near-IR (VNIR), shortwave-IR (SWIR), and thermal-IR (TIR) regions from 0.52 micron to 11.65 micron at high spatial resolutions of 15 m to 90 m. Stereo data will also be acquired in the VNIR region in a single band. The AVIRIS and TMS cover the ASTER VNIR and SWIR bands, and the TIMS covers the TIR bands. Simulated ASTER data sets have been generated over Death Valley, California, Cuprite, Nevada, and the Drum Mountains, Utah using a combination of AVIRIS, TIMS, amd TMS data, and existing digital elevation models (DEM) for the topographic information.

Mah, G. R.↗

Future Goddard data processing and data distribution systems

This paper discusses the current systems used at the Goddard Space Flight Center for processing spacecraft data, as well as the future system prospects. While current systems rely significantly on minicomputers, future systems will emphasize workstations. Space data formats will become more structured, and the increased application of space data standards will permit greater flexibilities in ground data processing, data distribution and savings in mission and data operations.

Koschmeder, Louis A.↗

The unified data system - A distributed processing network for control and data handling on a spacecraft

This paper presents the results obtained in a continuing investigation of real-time distributed processing systems which is being conducted at the Jet Propulsion Laboratory. A distributed processor architecture has been developed for control and data handling on a planetary spacecraft. This system, designated the Unified Data System, has been implemented in a feasibility breadboard. The following aspects of the Unified Data System are described: (1) standardized building block elements and their configuration into microprocessor modules, (2) a highly redundant bus structure which connects the various modules and facilitates intercommunications with minimal software support, (3) the structure of software within the individual modules and its coordination between modules, and (4) the mechanisms by which fault-tolerance can be implemented within the network. Through the attributes of multilevel standardization, simplicity, and flexibility, this system is expected to result in significant cost savings to future spacecraft missions.

Rennels, D. A.↗

Flight deck benefits of integrated data link communication

A fixed-base, piloted simulation study was conducted to determine the operational benefits that result when air traffic control (ATC) instructions are transmitted to the deck of a transport aircraft over a digital data link. The ATC instructions include altitude, airspeed, heading, radio frequency, and route assignment data. The interface between the flight deck and the data link was integrated with other subsystems of the airplane to facilitate data management. Data from the ATC instructions were distributed to the flight guidance and control system, the navigation system, and an automatically tuned communication radio. The co-pilot initiated the automation-assisted data distribution process. Digital communications and automated data distribution were compared with conventional voice radio communication and manual input of data into other subsystems of the simulated aircraft. Less time was required in the combined communication and data management process when data link ATC communication was integrated with the other subsystems. The test subjects, commercial airline pilots, provided favorable evaluations of both the digital communication and data management processes.

Waller, Marvin C.↗

Overview of the distributed image processing infrastructure to produce the Legacy Survey of Space and Time

The Vera C. Rubin Observatory is preparing to execute the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently the final phase of construction is under way in the Chilean Andes, with the Observatory’s ten-year science mission scheduled to begin in 2025. Rubin’s 8.4-meter telescope will nightly scan the southern hemisphere collecting imagery in the wavelength range 320–1050 nm covering the entire observable sky every 4 nights using a 3.2 gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this article we present an overview of the system currently being constructed to perform data distribution as well as the annual campaigns which reprocess the entire image dataset collected since the beginning of the survey. These processing campaigns will utilize computing and storage resources provided by three Rubin data facilities (one in the US and two in Europe). Each year a Data Release will be produced and disseminated to science collaborations for use in studies comprising four main science pillars: probing dark matter and dark energy, taking inventory of solar system objects, exploring the transient optical sky and mapping the Milky Way. Also presented is the method by which we leverage some of the common tools and best practices used for management of large-scale distributed data processing projects in the high energy physics and astronomy communities. We also demonstrate how these tools and practices are utilized within the Rubin project in order to overcome the specific challenges faced by the Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗

AIRSAR Automated Web-based Data Processing and Distribution System

In this paper, we present an integrated, end-to-end synthetic aperture radar (SAR) processing system that accepts data processing requests, submits processing jobs, performs quality analysis, delivers and archives processed data. This fully automated SAR processing system utilizes database and internet/intranet web technologies to allow external users to browse and submit data processing requests and receive processed data. It is a cost-effective way to manage a robust SAR processing and archival system. The integration of these functions has reduced operator errors and increased processor throughput dramatically.

WEB SERVICES↗

Data transfer for STAR grid jobs

The Solenoidal Tracker at RHIC (STAR) is a multipurpose experiment at the Relativistic Heavy Ion Collider (RHIC) with the primary goal to study the formation and properties of the quark-gluon plasma. STAR is an international collaboration of member institutions and laboratories from around the world. Yearly data-taking period produces PBytes of raw data collected by the experiment. STAR primarily uses its dedicated facility at BNL to process this data, but has routinely leveraged distributed systems, both high throughput (HTC) and high performance (HPC) computing clusters, to significantly augment the processing capacity available to the experiment. The ability to automate the efficient transfer of large data sets on reliable, scalable, and secure infrastructure is critical for any large-scale distributed processing campaign. For more than a decade, STAR computing has relied upon GridFTP with its x509-based authentication to build such data transfer systems and integrate them into its larger production workflow. The end of support by the community for both GridFTP and the x509 standard requires STAR to investigate other approaches to meet its distributed processing needs. In this study we investigate two multi-purpose data distribution systems, Globus.org and XRootD, as alternatives to GridFTP. We compare both their performance and the ease by which each service is integrated into the type of secure and automated data transfer systems STAR has previously built using GridFTP. The presented approach and study may be applicable to other distributed data processing use cases beyond STAR.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A distributed computing model for telemetry data processing

We present a new approach to distributing processed telemetry data among spacecraft flight controllers within the control centers at NASA's Johnson Space Center. This approach facilitates the development of application programs which integrate spacecraft-telemetered data and ground-based synthesized data, then distributes this information to flight controllers for analysis and decision-making. The new approach combines various distributed computing models into one hybrid distributed computing model. The model employs both client-server and peer-to-peer distributed computing models cooperating to provide users with information throughout a diverse operations environment. Specifically, it provides an attractive foundation upon which we are building critical real-time monitoring and control applications, while simultaneously lending itself to peripheral applications in playback operations, mission preparations, flight controller training, and program development and verification. We have realized the hybrid distributed computing model through an information sharing protocol. We shall describe the motivations that inspired us to create this protocol, along with a brief conceptual description of the distributed computing models it employs. We describe the protocol design in more detail, discussing many of the program design considerations and techniques we have adopted. Finally, we describe how this model is especially suitable for supporting the implementation of distributed expert system applications.

Barry, Matthew R.↗

A distributed processing high data rate multiport wind-tunnel pressure measurement system

A multiport pressure measurement system has been developed for the high data rates and the in situ calibration of electronically scanned pressure (ESP) sensors. The system employs a stand-alone microcomputer, connected to a host computer, for data acquisition and preprocessing. The host computer provides several operational modes. Before each run the in situ calibration of each sensor is automatically performed. Using up to a maximum of 14 data acquisition and control units (DACU's), the system may be expanded from 16 to 10,752 pressure ports. Each DACU can make 20,000 measurements per second, average data, and perform statistical analyses before transferring data to the central unit. The system may be introduced into existing facilities and requires little user orientation.

Juanarena, D.↗

Parallel Wavefront Analysis for a 4D Interferometer

This software provides a programming interface for automating data collection with a PhaseCam interferometer from 4D Technology, and distributing the image-processing algorithm across a cluster of general-purpose computers. Multiple instances of 4Sight (4D Technology s proprietary software) run on a networked cluster of computers. Each connects to a single server (the controller) and waits for instructions. The controller directs the interferometer to several images, then assigns each image to a different computer for processing. When the image processing is finished, the server directs one of the computers to collate and combine the processed images, saving the resulting measurement in a file on a disk. The available software captures approximately 100 images and analyzes them immediately. This software separates the capture and analysis processes, so that analysis can be done at a different time and faster by running the algorithm in parallel across several processors. The PhaseCam family of interferometers can measure an optical system in milliseconds, but it takes many seconds to process the data so that it is usable. In characterizing an adaptive optics system, like the next generation of astronomical observatories, thousands of measurements are required, and the processing time quickly becomes excessive. A programming interface distributes data processing for a PhaseCam interferometer across a Windows computing cluster. A scriptable controller program coordinates data acquisition from the interferometer, storage on networked hard disks, and parallel processing. Idle time of the interferometer is minimized. This architecture is implemented in Python and JavaScript, and may be altered to fit a customer s needs.

Rao, Shanti R.↗

Real-time simulation clock

The invention is a clock for synchronizing operations within a high-speed, distributed data processing network. The clock is actually a distributed system comprising a central clock and multiple site clock interface units (SCIUs) which are connected by means of a fiber optic star network and which operate under control of separate clock software. The presently preferred embodiment is a part of the flight simulation system now in current use at the NASA Langley Research Center.

Bennington, Donald R.↗