Reactors: A Data-Oriented Synchronous/Asynchronous Programming Model for Distributed Applications

2007 ◽  
pp. 76-95
Author(s):  
John Field ◽  
Maria-Cristina Marinescu ◽  
Christian Stefansen
Keyword(s):  
Programming Model ◽  
Distributed Applications ◽  
Asynchronous Programming

scholarly journals Reactors: A data-oriented synchronous/asynchronous programming model for distributed applications

2009 ◽  
Vol 410 (2-3) ◽  
pp. 168-201 ◽  
Author(s):  
John Field ◽  
Maria-Cristina Marinescu ◽  
Christian Stefansen
Keyword(s):  
Programming Model ◽  
Distributed Applications ◽  
Asynchronous Programming

Towards a Programming Model for Ubiquitous Computing

2011 ◽  
pp. 634-648
Author(s):  
Jorge Barbosa ◽  
Fabiane Dillenburg ◽  
Alex Garzão ◽  
Gustavo Lermen ◽  
Cristiano Costa
Keyword(s):  
Mobile Computing ◽  
Ubiquitous Computing ◽  
Context Awareness ◽  
Programming Model ◽  
Distributed Applications ◽  
Portable Devices ◽  
Heterogeneous Devices ◽  
The Core ◽  
Processing Power ◽  
Execution Environment

Mobile computing is been driven by the proliferation of portable devices and wireless communication. Potentially, in the mobile computing scenario, the users can move in different environments and the applications can automatically explore their surroundings. This kind of context-aware application is emerging, but is not yet widely disseminated. Based on perceived context, the application can modify its behavior. This process, in which software modifies itself according to sensed data, is named Adaptation. This constitutes the core of Ubiquitous Computing. The ubiquitous computing scenario brings many new problems such as coping with the limited processing power of mobile devices, frequent disconnections, the migration of code and tasks between heterogeneous devices, and others. Current practical approaches to the ubiquitous computing problem usually rely upon traditional computing paradigms conceived back when distributed applications where not a concern. Holoparadigm (in short Holo) was proposed as a model to support the development of distributed systems. Based on Holo concepts, a new programming language called HoloLanguage (in short, HoloL) was created. In this chapter, we propose the use of Holo for developing and executing ubiquitous applications. We explore the HoloL for ubiquitous programming and propose a full platform to develop and execute Holo programs. The language supports mobility, adaptation, and context awareness. The execution environment is based on a virtual machine that implements the concepts proposed by Holo. The environment supports distribution and strong code mobility.

Gears4Net An Asynchronous Programming Model

2009 ◽  
Author(s):  
Martin Saternus ◽  
Torben Weis ◽  
Sebastian Holzapfel ◽  
Arno Wacker
Keyword(s):  
Programming Model ◽  
Asynchronous Programming

Towards a Programming Model for Ubiquitous Computing

2012 ◽  
pp. 1744-1757
Author(s):  
Jorge Barbosa ◽  
Fabiane Dillenburg ◽  
Alex Garzão ◽  
Gustavo Lermen ◽  
Cristiano Costa
Keyword(s):  
Mobile Computing ◽  
Ubiquitous Computing ◽  
Context Awareness ◽  
Programming Model ◽  
Distributed Applications ◽  
Portable Devices ◽  
Heterogeneous Devices ◽  
The Core ◽  
Processing Power ◽  
Execution Environment

Mobile computing is been driven by the proliferation of portable devices and wireless communication. Potentially, in the mobile computing scenario, the users can move in different environments and the applications can automatically explore their surroundings. This kind of context-aware application is emerging, but is not yet widely disseminated. Based on perceived context, the application can modify its behavior. This process, in which software modifies itself according to sensed data, is named Adaptation. This constitutes the core of Ubiquitous Computing. The ubiquitous computing scenario brings many new problems such as coping with the limited processing power of mobile devices, frequent disconnections, the migration of code and tasks between heterogeneous devices, and others. Current practical approaches to the ubiquitous computing problem usually rely upon traditional computing paradigms conceived back when distributed applications where not a concern. Holoparadigm (in short Holo) was proposed as a model to support the development of distributed systems. Based on Holo concepts, a new programming language called HoloLanguage (in short, HoloL) was created. In this chapter, we propose the use of Holo for developing and executing ubiquitous applications. We explore the HoloL for ubiquitous programming and propose a full platform to develop and execute Holo programs. The language supports mobility, adaptation, and context awareness. The execution environment is based on a virtual machine that implements the concepts proposed by Holo. The environment supports distribution and strong code mobility.

scholarly journals Distributed data analysis with ROOT RDataFrame

2020 ◽  
Vol 245 ◽  
pp. 03009
Author(s):  
Vincenzo Eduardo Padulano ◽  
Javier Cervantes Villanueva ◽  
Enrico Guiraud ◽  
Enric Tejedor Saavedra
Keyword(s):  
Data Analysis ◽  
Programming Model ◽  
Distributed Processing ◽  
Distributed Applications ◽  
Distributed Data ◽  
Distributed Environments ◽  
Web Based ◽  
Intuitive Interface ◽  
Distributed Data Analysis

Widespread distributed processing of big datasets has been around for more than a decade now thanks to Hadoop, but only recently higher-level abstractions have been proposed for programmers to easily operate on those datasets, e.g. Spark. ROOT has joined that trend with its RDataFrame tool for declarative analysis, which currently supports local multi-threaded parallelisation. However, RDataFrame’s programming model is general enough to accommodate multiple implementations or backends: users could write their code once and execute it as-is locally or distributedly, just by selecting the corresponding backend. This abstract introduces PyRDF, a new python library developed on top of RDataFrame to seamlessly switch from local to distributed environments with no changes in the application code. In addition, PyRDF has been integrated with a service for web-based analysis, SWAN, where users can dynamically plug in new resources, as well as write, execute, monitor and debug distributed applications via an intuitive interface.

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