NDLI: A Self-Healing Framework for Online Sensor Data

Content Provider	IEEE Xplore Digital Library
Author	Nguyen, T.A. Aiello, M. Yonezawa, T. Tei, K.
Copyright Year	2015
Description	Author affiliation: Univ. of Groningen, Groningen, Netherlands (Nguyen, T.A.; Aiello, M.) \|\| Nat. Inst. of Inf., Tokyo, Japan (Tei, K.) \|\| Keio Univ., Tokyo, Japan (Yonezawa, T.)
Abstract	In pervasive computing environments, wireless sensor networks (WSNs) play an important role, collecting reliable and accurate context information so that applications are able to provide services to users on demand. In such environments, sensors should be self-adaptive by taking correct decisions based on sensed data in real-time. However, sensor data is often faulty. Faults are not so exceptional and in most deployments tend to occur frequently. Therefore, the capability of self-healing is important to ensure higher levels of reliability and availability. We design a framework which provides self-healing capabilities, enabling a flexible choice of components for detection, classification, and correction of faults at runtime. Within our framework, a variety of fault detection and classification algorithms can be applied, depending on the characteristics of the sensor data types as well as the topology of the sensor networks. A set of mechanisms for each and every step of the self-healing framework, covering detection, classification, and correction of faults are proposed. To validate the applicability, we illustrate a case study where our solution is implemented as an adaptation engine and integrated seamlessly into the ClouT system. The engine processes data coming from physical sensors deployed in Santander, Spain, providing corrected sensor data to other smart city applications developed in the ClouT project.
Starting Page	295
Ending Page	300
File Size	630906
Page Count	6
File Format	PDF
e-ISBN	9781467369718
DOI	10.1109/ICAC.2015.61
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-07
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cities and towns Monitoring Wireless sensor networks Data models Fault detection Knowledge based systems Data processing Smart environments Seal-healing framework Online sensor data Wireless sensor network Fault tolerance for WSNs
Content Type	Text
Resource Type	Article

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