21st IEEE/ACM International Conference on Automated Software Engineering (ASE'06) 2006
DOI: 10.1109/ase.2006.62
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Software Connectors for Highly Distributed and Voluminous Data Intensive Systems

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Cited by 9 publications
(9 citation statements)
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References 60 publications
(21 reference statements)
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“…In addition, we are collaborating with researchers identifying similar attributes to assess architectures for quality of service (QoS) parameters. One such QoS extension that is being incorporated in our tool is that on voluminous data intensive interactions [13]. It is important to note that these attributes must be periodically updated based on prevailing COTS characteristics.…”
Section: Discussionmentioning
confidence: 99%
“…In addition, we are collaborating with researchers identifying similar attributes to assess architectures for quality of service (QoS) parameters. One such QoS extension that is being incorporated in our tool is that on voluminous data intensive interactions [13]. It is important to note that these attributes must be periodically updated based on prevailing COTS characteristics.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, the amount of information exchanged in a distributed system can deeply influence the design of connector [Mattmann, 2007]. For example, P2P protocols are always chosen as communication mechanism of some connectors to deal with large scale data.…”
Section: Message Constructionmentioning
confidence: 99%
“…Based on a recent survey of data distribution experts [3], personalization approaches fall prey to the problem of organizational change -when domain experts leave an organization, they take their knowledge with them. In addition, because codification approaches (like DISCO) produce knowledge artifacts, such artifacts can be used as a shared means of recording key design decisions similar to the work of Capilla et al [10].…”
Section: Related Workmentioning
confidence: 99%
“…In addition, DISCO allows an architect to record observations about the performance of particular connectors in a given distribution scenario. We have currently developed three connector selection algorithms (the description of which is beyond the scope of this paper -see [3] for a complete description) that leverage our connector knowledge to pair connectors to distribution scenarios: Bayesian, Scored-based, and Optimizing [4]. Below we discuss how observation and insight are captured and used in greater detail.…”
Section: Related Workmentioning
confidence: 99%
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