Conference Paper

BeesyBees - Efficient and Reliable Execution of Service-based Workflow Applications for BeesyCluster using Distributed Agents

Fac. of Electron. Telecommun. & Inf., Gdansk Univ. of Technol., Gdansk, Poland
Conference: International Multiconference on Computer Science and Information Technology - IMCSIT 2010, Wisla, Poland, 18-20 October 2010, Proceedings
Source: DBLP


The paper presents an architecture and implementation that allows distributed execution of workflow applications in BeesyCluster using agents. BeesyCluster is a middleware that allows users to access distributed resources as well as publish applications as services, define service costs, grant access to other users and consume services published by others. Workflows created in the BeesyCluster middleware are exported to BPEL and executed by agents in a distributed environment. As a proof of concept, we have implemented a real workflow for parallel processing of digital images and tested it in a real cluster-based environment. Firstly, we demonstrate that engaging several agents for distributed execution is more efficient than a centralized approach.We also show increasing negotiation time in case of too many agents. Secondly, we demonstrate that execution in the proposed environment is reliable even in case of failures. If a service fails, a task agent picks a new equivalent service at runtime. If one of task agents fails, another of remaining agents takes over its responsibilities. The communication between the middleware, agents and services is encrypted.

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    ABSTRACT: The paper presents a concept and an implementation of dynamic learning of compatibilities of services used in a workflow application. While services may have the same functionality, they may accept input and produce output in different formats. The proposed solution learns matching of outputs and inputs at runtime and uses this knowledge in subsequent runs of workflow applications. The presented solution was implemented in an existing workflow execution system - BeesyBees.