Near real time weather and ocean model data access with rNOMADS

2015 ◽  
Vol 78 ◽  
pp. 88-95 ◽  
Author(s):  
D.C. Bowman ◽  
J.M. Lees
Keyword(s):  
Real Time ◽  
Data Access ◽  
Ocean Model ◽  
Model Data

scholarly journals Technical note: Harmonizing met-ocean model data via standard web services within small research groups

2015 ◽  
Vol 12 (6) ◽  
pp. 2655-2682
Author(s):  
R. P. Signell ◽  
E. Camossi
Keyword(s):  
Web Services ◽  
Data Access ◽  
Ocean Model ◽  
Technical Note ◽  
Service Access ◽  
Research Groups ◽  
Model Data ◽  
Us Government ◽  
Access To Data ◽  
Abstract Work

Abstract. Work over the last decade has resulted in standardized web-services and tools that can significantly improve the efficiency and effectiveness of working with meteorological and ocean model data. While many operational modelling centres have enabled query and access to data via common web services, most small research groups have not. The penetration of this approach into the research community, where IT resources are limited, can be dramatically improved by: (1) making it simple for providers to enable web service access to existing output files; (2) using technology that is free, and that is easy to deploy and configure; and (3) providing tools to communicate with web services that work in existing research environments. We present a simple, local brokering approach that lets modelers continue producing custom data, but virtually aggregates and standardizes the data using NetCDF Markup Language. The THREDDS Data Server is used for data delivery, pycsw for data search, NCTOOLBOX (Matlab®1) and Iris (Python) for data access, and Ocean Geospatial Consortium Web Map Service for data preview. We illustrate the effectiveness of this approach with two use cases involving small research modelling groups at NATO and USGS.1 Mention of trade names or commercial products does not constitute endorsement or recommendation for use by the US Government.

scholarly journals Technical note: Harmonising metocean model data via standard web services within small research groups

Ocean Science ◽  
2016 ◽  
Vol 12 (3) ◽  
pp. 633-645 ◽  
Author(s):  
Richard P. Signell ◽  
Elena Camossi
Keyword(s):  
Web Services ◽  
Data Access ◽  
Ocean Model ◽  
Technical Note ◽  
Service Access ◽  
Research Groups ◽  
Model Data ◽  
Operational Modelling ◽  
Access To Data ◽  
Abstract Work

Abstract. Work over the last decade has resulted in standardised web services and tools that can significantly improve the efficiency and effectiveness of working with meteorological and ocean model data. While many operational modelling centres have enabled query and access to data via common web services, most small research groups have not. The penetration of this approach into the research community, where IT resources are limited, can be dramatically improved by (1) making it simple for providers to enable web service access to existing output files; (2) using free technologies that are easy to deploy and configure; and (3) providing standardised, service-based tools that work in existing research environments. We present a simple, local brokering approach that lets modellers continue to use their existing files and tools, while serving virtual data sets that can be used with standardised tools. The goal of this paper is to convince modellers that a standardised framework is not only useful but can be implemented with modest effort using free software components. We use NetCDF Markup language for data aggregation and standardisation, the THREDDS Data Server for data delivery, pycsw for data search, NCTOOLBOX (MATLAB®) and Iris (Python) for data access, and Open Geospatial Consortium Web Map Service for data preview. We illustrate the effectiveness of this approach with two use cases involving small research modelling groups at NATO and USGS.

Secure Real-time Data Access Using Two-Factor Authentication Scheme for the Internet of Drones

2021 ◽  
Author(s):  
Haqi Khalid ◽  
Shaiful Jahari Hashim ◽  
Sharifah Mumtazah Syed Ahamed ◽  
Fazirulhisyam Hashim ◽  
Muhammad Akmal Chaudhary
Keyword(s):  
Real Time ◽  
Data Access ◽  
Authentication Scheme ◽  
The Internet ◽  
Time Data ◽  
Real Time Data

scholarly journals OceanSpy: A Python package to facilitate ocean model data analysis and visualization

2019 ◽  
Vol 4 (39) ◽  
pp. 1506 ◽  
Author(s):  
Mattia Almansi ◽  
Renske Gelderloos ◽  
Thomas Haine ◽  
Atousa Saberi ◽  
Ali Siddiqui
Keyword(s):  
Data Analysis ◽  
Ocean Model ◽  
Model Data ◽  
Python Package

Memory-Aware Scheduling Parallel Real-Time Tasks for Multicore Systems

2021 ◽  
Vol 31 (04) ◽  
pp. 613-634
Author(s):  
Zhenyang Lei ◽  
Xiangdong Lei ◽  
Jun Long
Keyword(s):  
Real Time ◽  
Data Access ◽  
Main Memory ◽  
Second Phase ◽  
Shared Resources ◽  
Access Memory ◽  
Worst Case ◽  
Scheduling Policy ◽  
The Core ◽  
Level Scheduling

Shared resources on the multicore chip, such as main memory, are increasingly becoming a point of contention. Traditional real-time task scheduling policies focus on solely on the CPU, and do not take in account memory access and cache effects. In this paper, we propose parallel real-time tasks scheduling (PRTTS) policy on multicore platforms. Each set of tasks is represented as a directed acyclic graph (DAG). The priorities of tasks are assigned according to task periods Rate Monotonic (RM). Each task is composed of three phases. The first phase is read memory stage, the second phase is execution phase and the third phase is write memory phase. The tasks use locks and critical sections to protect data access. The global scheduler maintains the task pool in which tasks are ready to be executed which can run on any core. PRTTS scheduling policy consists of two levels: the first level scheduling schedules ready real-time tasks in the task pool to cores, and the second level scheduling schedules real-time tasks on cores. Tasks can preempt the core on running tasks of low priority. The priorities of tasks which want to access memory are dynamically increased above all tasks that do not access memory. When the data accessed by a task is in the cache, the priority of the task is raised to the highest priority, and the task is scheduled immediately to preempt the core on running the task not accessing memory. After accessing memory, the priority of these tasks is restored to the original priority and these tasks are pended, the preempted task continues to run on the core. This paper analyzes the schedulability of PRTTS scheduling policy. We derive an upper-bound on the worst-case response-time for parallel real-time tasks. A series of extensive simulation experiments have been performed to evaluate the performance of proposed PRTTS scheduling policy. The results of simulation experiment show that PRTTS scheduling policy offers better performance in terms of core utilization and schedulability rate of tasks.

scholarly journals ACCESS TO DIGITAL CAR DATA AND COMPETITION IN AFTERMARKET MAINTENANCE SERVICES

2020 ◽  
Vol 16 (1) ◽  
pp. 116-141
Author(s):  
Bertin Martens ◽  
Frank Mueller-Langer
Keyword(s):  
Real Time ◽  
Network Effects ◽  
Economies Of Scale ◽  
Service Providers ◽  
Data Access ◽  
Third Party ◽  
Similar Data ◽  
Time Data ◽  
Price Discriminate ◽  
Data Portability

Abstract Before the arrival of digital car data, car manufacturers had already partly foreclosed the maintenance market through franchising contracts with a network of exclusive official dealers. EU regulation endorsed this foreclosure but mandated access to maintenance data for independent service providers to keep competition in these markets. The arrival of digital car data upsets this balance because manufacturers can collect real-time maintenance data on their servers and send messages to drivers. These can be used to price discriminate and increase the market share of official dealers. There are at least four alternative technical gateways that could give independent service providers similar data access options. However, they suffer in various degrees from data portability issues, switching costs and weak network effects, and insufficient economies of scale and scope in data analytics. Multisided third-party consumer media platforms appear to be better placed to overcome these economic hurdles, provided that an operational real-time data portability regime could be established.

Sign in / Sign up

Export Citation Format

Share Document