ABSTRACT
Proliferation of IoT (Internet of Things) and sensor technology has expedited the realization of Smart City. To enable necessary functions, sensors distributed across the city generate a huge volume of stream data that are crucial for controlling Smart City devices. However, due to conditions such as wears and tears, battery drain, or malicious attacks, not all data are reliable even when they are accurately measured. These data could lead to invalid and devastating consequences (e.g., failed utility or transportation services). The assessment of data reliability is necessary and challenging especially for Smart City, as it has to keep up with velocity of big data stream to provide up-to-date results. Most research on data reliability has focused on data fusion and anomaly detection that lack a quantified measure of how much the data over a period of time are adequately reliable for decision-makings. This paper alleviates these issues and presents an online approach to assessing Big stream data reliability in a timely manner. By employing a well-studied evidence-based theory, our approach provides a computational framework that assesses data reliability in terms of belief likelihoods. The framework is lightweight and easy to scale, deeming fit for streaming data. We evaluate the approach using a real application of light sensing data of 1,323,298 instances. The preliminary results are consistent with logical rationales, confirming validity of the approach.
- Atzori, L., Iera, A., and Morabito, G. 2010. The internet of things: A survey. Computer networks. 54(15), 2787--2805.Google Scholar
- Array of Things. 2019. Array of Things Data Set and Specification Sheet. URL: https://aot-file-browser.plenar.io/data-sets/chicago-completeGoogle Scholar
- Jiang, W., Zhuang, M., and Xie, C. 2017. A reliability-based method to sensor data fusion. Sensors. 17(7), 1575.Google ScholarCross Ref
- Pollock, J. L. 1984. Reliability and justified belief. Canadian Journal of Philosophy. 14 (1): 103--114.Google ScholarCross Ref
- Rogova, G. L., and Nimier, V. 2004. Reliability in information fusion: literature survey. In Procs. of the 7th inter. conf. on information fusion. Vol. 2, pp. 1158--1165.Google Scholar
- Shafer, G. 1976. A Mathematical Theory of Evidence. Princeton University Press.Google Scholar
- Sheikh, A. A., Lbath, A., Warriach, E. U., and Felemban, E. 2015. A Predictive Data Reliability Method for Wireless Sensor Network Applications. In Inter. Conf. on Alg. and Arch. for Parallel Processing. 648--658. Springer, Cham.Google Scholar
- Wang, B., Zeng, C., and Wu, P. 2010. Evidence modeling based on sensor credibility. In 2010 Inter. Symp. on Comp.l Intelli. and Design, 2, 148--151. IEEE.Google Scholar
- Yuan, K., Xiao, F., Fei, L., Kang, B., and Deng, Y. 2016. Modeling sensor reliability in fault diagnosis based on evidence theory. Sensors. 16(1), 113.Google ScholarCross Ref
- Zhang, Y., Meratnia, N., and Havinga, P. J. 2010. Outlier detection techniques for wireless sensor networks: A survey. IEEE Com. Surveys and Tutorials, 12(2), 159--170.Google ScholarDigital Library
- Zhang, Z., Mehmood, A., Shu, L., Huo, Z., Zhang, Y., and Mukherjee, M. 2018. A survey on fault diagnosis in wireless sensor networks, IEEE Access, 6, 11349--1136Google ScholarCross Ref
Index Terms
- Assessing Reliability of Big Data Stream for Smart City
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