
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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| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
