Research Article
DQS-Cloud: A Data Quality-Aware Autonomic Cloud for Sensor Services
@INPROCEEDINGS{10.4108/icst.collaboratecom.2014.257475, author={Abhishek Kothari and Vinay Boddula and Lakshmish Ramaswamy and Neda Abolhassani}, title={DQS-Cloud: A Data Quality-Aware Autonomic Cloud for Sensor Services}, proceedings={10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing}, publisher={IEEE}, proceedings_a={COLLABORATECOM}, year={2014}, month={11}, keywords={internet of things data quality sensor service discovery feed processing plan}, doi={10.4108/icst.collaboratecom.2014.257475} }- Abhishek Kothari
Vinay Boddula
Lakshmish Ramaswamy
Neda Abolhassani
Year: 2014
DQS-Cloud: A Data Quality-Aware Autonomic Cloud for Sensor Services
COLLABORATECOM
IEEE
DOI: 10.4108/icst.collaboratecom.2014.257475
Abstract
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 real-time. 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.