2016Unpublished venueRequires access

Tasklets: Overcoming Heterogeneity in Distributed Computing Systems

Dominik Schäfer, Janick Edinger, Sebastian VanSyckel, Justin Mazzola Paluska, Christian Becker

Open publisher page 19 citations

Abstract

Distributed computing is a good alternative to expensive supercomputers. There are plenty of frameworks that enable programmers to harvest remote computing power. However, until today, much computation power in the edges of the Internet remains unused. While idle devices could contribute to a distributed environment as generic computation resources, computation-intense applications could use this pool of resources to enhance their execution quality. In this paper, we identify heterogeneity as a major burden for distributed and edge computing. Heterogeneity is present in multiple forms. We draw our vision of a comprehensive distributed computing system and show where existing frameworks fall short in dealing with the heterogeneity of distributed computing. Afterwards, we present the Tasklet system, our approach for a distributed computing framework. Tasklets are fine-grained computation units that can be issued for remote and local execution. We tackle the different dimensions of heterogeneity and show how to make use of available computation power in edge resources. In our prototype, we use middleware and virtualization technologies as well as a host language concept.

About this research paper

What this paper is about

Distributed computing is a good alternative to expensive supercomputers. There are plenty of frameworks that enable programmers to harvest remote computing power. However, until today, much computation power in the edges of the Internet remains unused. While idle devices could contribute to a distributed environment as generic computation resources, computation-intense applications could use this pool of resources to enhance their execution quality. In this paper, we identify heterogeneity as a major burden for distributed and edge computing. Heterogeneity is present in multiple forms. We draw our vision of a comprehensive distributed computing system and show where existing frameworks fall short in dealing with the heterogeneity of distributed computing. Afterwards, we present the Tasklet system, our approach for a distributed computing framework. Tasklets are fine-grained computation units that can be issued for remote and local execution. We tackle the different dimensions of heterogeneity and show how to make use of available computation power in edge resources. In our prototype, we use middleware and virtualization technologies as well as a host language concept.

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OpenAlex reports 19 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Distributed computing is a good alternative to expensive supercomputers. There are plenty of frameworks that enable programmers to harvest remote computing power. However, until today, much computation power in the edges of the Internet remains unused. While idle devices could contribute to a distributed environment as generic computation resources, computation-intense applications could use this pool of resources to enhance their execution quality. In this paper, we identify heterogeneity as a major burden for distributed and edge computing. Heterogeneity is present in multiple forms. We draw our vision of a comprehensive distributed computing system and show where existing frameworks fall short in dealing with the heterogeneity of distributed computing. Afterwards, we present the Tasklet system, our approach for a distributed computing framework. Tasklets are fine-grained computation units that can be issued for remote and local execution. We tackle the different dimensions of heterogeneity and show how to make use of available computation power in edge resources. In our prototype, we use middleware and virtualization technologies as well as a host language concept.

Key concepts: Computer science, Distributed computing, Computation, Virtualization, Symmetric multiprocessor system, Edge computing, Middleware (distributed applications), Enhanced Data Rates for GSM Evolution

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