A Chemical Based Middleware for Workflow Instantiation and Execution

Napoli, Claudia Di; Giordano, Maurizio; Pazat, Jean-Louis; Wang, Chen

doi:10.1007/978-3-642-17694-4_9

Cited by 6 publications

(7 citation statements)

References 16 publications

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“…The chemical computing model is an upcoming candidate for realizing autonomic properties in various distributed settings (such as grid and service based environments, see [5] [11] [18]). …”

Section: Discussionmentioning

confidence: 99%

“…Grids are obviously a good target for applying the chemical model in some well-known problems like coordinating a ray-tracing example on desktop grids [7], enacting workflows on-the-fly with strong emphasis on dynamicity both in the environment and in the workflow structure [11] and modeling self-developing secure virtual organisations [2]. Recently service oriented techniques and clouds also attracted great attention and proposals like chemical based service orchestration [6], dynamic service composition [5], dynamic service composition with partial instantiations and re-using instantiations [18] and others. Note, that the chemical model in all these cases is not applied for problem solving (in terms of solving any computational tasks) but coordinates the execution so that it may exhibit some of the features of the chemical metaphor like timely response to events, adaptation, self-evolution, intrinsic concurrency, independency, maximum parallelism and many others.…”

Section: Introductionmentioning

confidence: 99%

“…The work is focusing on the design and realization of the interpreter. Establishing autonomic or adaptive behaviour in the chemical framework is on one hand presented in papers [7][11] [5][8] [18], etc., on the other hand related to the application of the interpreter and not presented here.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Chemical Machine: An Interpreter for the Higher Order Chemical Language

Rajcsányi

Németh

2012

Euro-Par 2011: Parallel Processing Workshops

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Abstract. The notion of chemical computing has evolved for more than two decades. From the seminal idea several models, calculi and languages have been developed and there are various proposals for applying chemical models in distributed problem solving where some sort of autonomy, self-evolving nature and adaptation is sought. While there are some experimental chemical implementations, most of these proposals remained at the paper-and-pencil stage. This paper presents a general purpose interpreter for the Higher Order Chemical Language. The design follows that of logic/functional languages and bridges the gap between the highly abstract chemical model and the physical machine by an abstract interpreter engine. As a novel approach the engine is based on a modified hierarchical production system and turns away from imperative languages.

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“…The chemical computing model is an upcoming candidate for realizing autonomic properties in various distributed settings (such as grid and service based environments, see [5] [11] [18]). …”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Chemical Machine: An Interpreter for the Higher Order Chemical Language

Rajcsányi

Németh

2012

Euro-Par 2011: Parallel Processing Workshops

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“…While this example is quite simple, it already provides the intuition behind autonomic coordination and adaptation, and its simple programming style. These features are explored in more detail in [15,16,17]. Furthermore, as a rule-based language, HOCL provides a high level of abstraction for the modelling of the service interactions, as rules allow to define the collaborations without having to interact with the individual services.…”

Section: 07mentioning

confidence: 99%

Rule-driven service coordination middleware for scientific applications

Fernández¹,

Tedeschi²,

Priol³

2014

Future Generation Computer Systems

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International audienceWith the proliferation of Web services, scientific applications are more and more designed as temporal compositions of services, commonly referred to as workflows. To address this paradigm shift, different workflow management systems have been proposed. While their efficiency has been established over centralized static systems, it is questionable over decentralized failure-prone platforms. Scientific applications recently started to be deployed over large distributed computing platforms, leading to new issues, like elasticity, i.e., the possibility to dynamically refine, at runtime, the amount of resources dedicated to an application. This raised again the demand for new programming models, able to express autonomic self-coordination of services in a dynamic platform. Nature-inspired, rule-based computing models recently gained a lot of attention in this context. They are able to naturally expressing parallelism, distribution, and autonomic adaptation. While their high expressiveness and adequacy for this context has been established, such models severely suffer from a lack of proof of concepts. In this paper, we concretely show how to leverage such models in this context. We focus on the design, the implementation and the experimental validation of a chemistry-inspired scientific workflow management system

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“…This has been the subject of a growing number of studies [4], [5], [6]. However, while the benefits of such a paradigm has been established, its deployment at large scale still remains a widely open issue, hindering the model to be actually used.…”

Section: Introductionmentioning

confidence: 98%

When Distributed Hash Tables Meet Chemical Programming for Autonomic Computing

Obrovac¹,

Tedeschi²

2012

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops &Amp; PhD Forum

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With the rise of Service Computing, applications are more and more built as temporal compositions of autonomous services, in which services are combined dynamically to satisfy constantly arriving users' requests. These applications run on top of web-based, large, unreliable, and heterogeneous platforms, in which there is a high demand for autonomic behaviours, such as selfoptimisation, self-adaptation, or self-healing.Chemistry-inspired computing consists in envisioning a computation as a succession of implicitly parallel, distributed and autonomous reactions, each reaction consuming molecules of data to produce new ones, until the state of inertia, where no more reactions are possible. This vision of a computation makes it a promising candidate to inject autonomic behaviours in service computing.However, while the benefits of such a model are manifold, its deployment over large scale platforms remains a widely open issue. In this paper, after identifying the main obstacles towards such a deployment, we propose a peer-to-peer framework able to execute chemical specifications at large scale. It combines distributed hash tables and algorithms for the atomic capture of molecules, and proposes an efficient method for inertia detection, which is a critical problem, in particular when addressed in a large scale environment. The sustainability of the framework is established through a complete complexity analysis.

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A Chemical Based Middleware for Workflow Instantiation and Execution

Cited by 6 publications

References 16 publications

The Chemical Machine: An Interpreter for the Higher Order Chemical Language

The Chemical Machine: An Interpreter for the Higher Order Chemical Language

Rule-driven service coordination middleware for scientific applications

When Distributed Hash Tables Meet Chemical Programming for Autonomic Computing

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