Chemical Computing for Distributed Systems: Algorithms and Implementation

Marko Obrovac 1
1 MYRIADS - Design and Implementation of Autonomous Distributed Systems
IRISA-D1 - SYSTÈMES LARGE ÉCHELLE, Inria Rennes – Bretagne Atlantique
Abstract : With the emergence of highly heterogeneous, dynamic and large distributed platforms, the need for a way to efficiently program and manage them has arisen. The concept of autonomic computing proposes to create self-manageable systems --- systems which are aware of their components and their environment, and can configure, optimise, heal and protect themselves. In the context of realisation of such systems, declarative programming, whose goal is to ease the programmer's task by separating the control from the logic of a computation, has regained a lot of interest recently. In particular, rule-based programming is regarded as a promising model in this quest for adequate programming abstractions for these platforms. However, while these models are gaining a lot of attention, there is a demand for generic tools able to run such models at large scale. The chemical programming model, which was designed following the chemical metaphor, is a higher-order, rule-based programming model, with a non-deterministic execution model, where rules are applied concurrently on a multiset of data. In this thesis, we propose the design, development, and experimentation of a distributed chemical runtime for generic, largely-distributed platforms. The architecture proposed combines a peer-to-peer communication layer with an adaptive protocol for atomically capturing objects on which rules should be applied, and an efficient termination-detection scheme. We describe the software prototype implementing this architecture. Based on its deployment over a real-world test-bed, we present its performance results, which confirm analytically obtained complexities, and experimentally show the sustainability of such a programming model.
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Marko Obrovac. Chemical Computing for Distributed Systems: Algorithms and Implementation. Calcul parallèle, distribué et partagé [cs.DC]. Université Rennes 1, 2013. Français. ⟨tel-00925257⟩

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