Promote-IT: An efficient Real-Time Tertiary-Storage Scheduler

Promote-IT is an efficient heuristic scheduler that provides QoS guarantees for accessing data from tertiary storage. It can deal with a wide variety of requests and jukebox hardware. It provides short response and confirmation times, and makes good use of the jukebox resources. It separates the scheduling and dispatching functionality and effectively uses this separation to dispatch tasks earlier than scheduled, provided that the resource constraints are respected and no task misses its deadline. To prove the efficiency of Promote-IT we implemented alternative schedulers based on different scheduling models and scheduling paradigms. The evaluation shows that Promote-IT performs better than the other heuristic schedulers. Additionally, Promote-IT provides response-times near the optimum in cases where the optimal scheduler can be computed

ViPEr-HiSS: A Case for Storage Design Tools

The viability of large-scale multimedia applications, depends on the performance of storage systems. Providing cost-effective access to vast amounts of video, image, audio, and text data, requires (a) proper configuration of storage hierarchies as well as (b) efficient resource management techniques at all levels of the storage hierarchy. The resulting complexities of the hardware/software co-design in turn contribute to difficulties in making accurate predictions about performance, scalability, and cost-effectiveness of a storage system. Moreover, poor decisions at design time can be costly and problematic to correct in later stages of development. Hence, measurement of systems after they have been developed is not a desirable approach to predicting their performance. What is needed is the ability to evaluate the system's design while there are still opportunities to make corrections to fundamental design flaws. In this paper we describe the framework of ViPEr-HiSS, a tool which facilitates design, development, and subsequent performance evaluation of designs of multimedia storage hierarchies by providing mechanisms for relatively easy experimentation with (a) system configurations as well as (b) application- and media-aware resource management techniques. (Also cross-referenced as UMIACS-TR-99-69

On-line data archives

©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Digital libraries and other large archives of electronically retrievable and manipulable material are becoming widespread in both commercial and scientific arenas. Advances in networking technologies have led to a greater proliferation of wide-area distributed data warehousing with associated data management challenges. We review tools and technologies for supporting distributed on-line data archives and explain our key concept of active data archives, in which data can be, processed on-demand before delivery. We are developing wide-area data warehousing software infrastructure for geographically distributed archives of large scientific data sets, such as satellite image data, that are stored hierarchically on disk arrays and tape silos and are accessed by a variety of scientific and decision support applications. Interoperability is a major issue for distributed data archives and requires standards for server interfaces and metadata. We review present activities and our contributions in developing such standards for different application areas.K. Hawick, P. Coddington, H. James, C. Patte

Sixth Goddard Conference on Mass Storage Systems and Technologies Held in Cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems

This document contains copies of those technical papers received in time for publication prior to the Sixth Goddard Conference on Mass Storage Systems and Technologies which is being held in cooperation with the Fifteenth IEEE Symposium on Mass Storage Systems at the University of Maryland-University College Inn and Conference Center March 23-26, 1998. As one of an ongoing series, this Conference continues to provide a forum for discussion of issues relevant to the management of large volumes of data. The Conference encourages all interested organizations to discuss long term mass storage requirements and experiences in fielding solutions. Emphasis is on current and future practical solutions addressing issues in data management, storage systems and media, data acquisition, long term retention of data, and data distribution. This year's discussion topics include architecture, tape optimization, new technology, performance, standards, site reports, vendor solutions. Tutorials will be available on shared file systems, file system backups, data mining, and the dynamics of obsolescence

Survey of semi-regular multiresolution models for interactive terrain rendering

Rendering high quality digital terrains at interactive rates requires carefully crafted algorithms and data structures able to balance the competing requirements of realism and frame rates, while taking into account the memory and speed limitations of the underlying graphics platform. In this survey, we analyze multiresolution approaches that exploit a certain semi-regularity of the data. These approaches have produced some of the most efficient systems to date. After providing a short background and motivation for the methods, we focus on illustrating models based on tiled blocks and nested regular grids, quadtrees and triangle bin-trees triangulations, as well as cluster-based approaches. We then discuss LOD error metrics and system-level data management aspects of interactive terrain visualization, including dynamic scene management, out-of-core data organization and compression, as well as numerical accurac

Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective

Machine Learning models are being deployed as parts of real-world systems with the upsurge of interest in artificial intelligence. The design, implementation, and maintenance of such systems are challenged by real-world environments that produce larger amounts of heterogeneous data and users requiring increasingly faster responses with efficient resource consumption. These requirements push prevalent software architectures to the limit when deploying ML-based systems. Data-oriented Architecture (DOA) is an emerging concept that equips systems better for integrating ML models. DOA extends current architectures to create data-driven, loosely coupled, decentralised, open systems. Even though papers on deployed ML-based systems do not mention DOA, their authors made design decisions that implicitly follow DOA. The reasons why, how, and the extent to which DOA is adopted in these systems are unclear. Implicit design decisions limit the practitioners' knowledge of DOA to design ML-based systems in the real world. This paper answers these questions by surveying real-world deployments of ML-based systems. The survey shows the design decisions of the systems and the requirements these satisfy. Based on the survey findings, we also formulate practical advice to facilitate the deployment of ML-based systems. Finally, we outline open challenges to deploying DOA-based systems that integrate ML models.Comment: Under revie

Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distribution

Digital Twins are digital replica of real entities and are becoming fundamental tools to monitor and control the status of entities, predict their future evolutions, and simulate alternative scenarios to understand the impact of changes. Thanks to the large deployment of sensors, with the increasing information it is possible to build accurate reproductions of urban environments including structural data and real-time information. Such solutions help city councils and decision makers to face challenges in urban development and improve the citizen quality of life, by ana-lysing the actual conditions, evaluating in advance through simulations and what-if analysis the outcomes of infrastructural or political chang-es, or predicting the effects of humans and/or of natural events. Snap4City Smart City Digital Twin framework is capable to respond to the requirements identified in the literature and by the international forums. Differently from other solutions, the proposed architecture provides an integrated solution for data gathering, indexing, computing and information distribution offered by the Snap4City IoT platform, therefore realizing a continuously updated Digital Twin. 3D building models, road networks, IoT devices, WoT Entities, point of interests, routes, paths, etc., as well as results from data analytical processes for traffic density reconstruction, pollutant dispersion, predictions of any kind, what-if analysis, etc., are all integrated into an accessible web interface, to support the citizens participation in the city decision processes. What-If analysis to let the user performs simulations and observe possible outcomes. As case of study, the Digital Twin of the city of Florence (Italy) is presented. Snap4City platform, is released as open-source, and made available through GitHub and as docker compose

Public Commons for Geospatial Data: A Conceptual Model

A wide variety of spatial data collection efforts are ongoing throughout local, state and federal agencies, private firms and non-profit organizations. Each effort is established for a different purpose but organizations and individuals often collect and maintain the same or similar information. The United States federal government has undertaken many initiatives such as the National Spatial Data Infrastructure, the National Map and Geospatial One-Stop to reduce duplicative spatial data collection and promote the coordinated use, sharing, and dissemination of spatial data nationwide. A key premise in most of these initiatives is that no national government will be able to gather and maintain more than a small percentage of the geographic data that users want and desire. Thus, national initiatives depend typically on the cooperation of those already gathering spatial data and those using GIs to meet specific needs to help construct and maintain these spatial data infrastructures and geo-libraries for their nations (Onsrud 2001). Some of the impediments to widespread spatial data sharing are well known from directly asking GIs data producers why they are not currently involved in creating datasets that are of common or compatible formats, documenting their datasets in a standardized metadata format or making their datasets more readily available to others through Data Clearinghouses or geo-libraries. The research described in this thesis addresses the impediments to wide-scale spatial data sharing faced by GIs data producers and explores a new conceptual data-sharing approach, the Public Commons for Geospatial Data, that supports user-friendly metadata creation, open access licenses, archival services and documentation of parent lineage of the contributors and value- adders of digital spatial data sets

Opnet, Arne, and the Classroom

This paper examines OPNET Technology, Inc\u27s management programs, and Regis University\u27s Academic Research Network (ARNe) needs to find out which OPNET programs can meet the needs of ARNe. The method used was to examine ARNe\u27s needs, and research Microsoft\u27s SMF/MOF management framework, research OPNET\u27s program and module offerings, research OPNET\u27s University Program, and research how OPNET\u27s programs are used at some other universities. The research was used to create a match up between Microsoft\u27s Service Management Functions and OPNET\u27s programs and modules. And it was used to create a list of textbooks, labs, and lab manuals that would work with OPNET\u27s IT Guru and Modeler in a classroom to help teach networking theory. The examination was combined with the research to create an evaluation criteria matrix from which project recommendations could be drawn. The conclusion was that the following OPNET Technology programs and modules could be of benefit to Regis University\u27s ARNe - ACE, Automation module, Commander, DAC module, Flow Analysis module, IT Sentinel, IT Guru, NetDoctor, Report Server, and VNE Server