Query planning & adaptation in Data Quality-Aware Sensor Services Cloud
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With the advent of Internet of Things, the field of domain sensing is increasingly being ‘servitized’. In order to effectively support this servitization, there is a growing need for a powerful and easy-to-use infrastructure that enables seamless sharing of sensor data in realtime. In this paper, we present the design and evaluation of Data Quality-Aware Sensor Cloud (DQS-Cloud), a cloud-based sensor data services infrastructure. DQS-Cloud is characterized by three novel features. First, data-quality is pervasive throughout the infrastructure ranging from feed discovery to failure resilience. Second, it incorporates autonomic-computing-based techniques for dealing with sensor failures as well as data quality dynamics. Third, DQS-Cloud also features a unique sensor stream management engine that optimizes the system performance by dynamically placing stream management operators. This paper reports several experiments to study the effectiveness and the efficiency of the framework.