Service Intelligence Oriented Distributed Data Stream Integration
Feng-Lin Li, Chi-Hung Chi, Yue Wang, Cong Liu

TL;DR
This paper presents a comprehensive approach for integrating distributed data streams in service-oriented architectures, addressing synchronization, aggregation, and performance evaluation to meet real-time SaaS requirements.
Contribution
It introduces systematic strategies for relating distributed data, a novel small window array mechanism, CDF-based window parameter setting, and queuing models for performance prediction.
Findings
High accuracy and completeness in distributed data stream processing
Effective aggregation of distributed service data streams
Acceptable performance metrics in real-time scenarios
Abstract
Software as a service (SaaS) has recently enjoyed much attention as it makes the use of software more convenient and cost-effective. At the same time, the arising of users' expectation for high quality service such as real-time information or functionality provisioning brings about new challenges: to satisfy such (near) real-time requirements, real-time monitoring and effective processing of streaming data is necessary. However, due to the composition structure and multi-instance property of services, service data streams are often distributed, hard to synchronize and aggregate. We tackles these challenges by (1) proposing systematic associate strategies for relating distributed data; (2) introducing a new small window array mechanism for aggregating distributed data; (3) setting window parameters based on the cumulative distribution function (CDF) method; and (4) modeling streaming…
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Taxonomy
TopicsAdvanced Database Systems and Queries · Data Management and Algorithms · Service-Oriented Architecture and Web Services
