Paper Info
Title
A Self-Healing Framework for Online Sensor Data
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.
Year
DOI
Venue
2015
10.1109/ICAC.2015.61
International Conference on Autonomic Computing
Keywords
Field
DocType
Seal-healing framework,Online sensor data,Wireless sensor network,Fault tolerance for WSNs,Smart environments
Key distribution in wireless sensor networks,Data modeling,Smart environment,Fault detection and isolation,Computer science,Real-time computing,Smart city,Ubiquitous computing,Statistical classification,Wireless sensor network,Distributed computing
Conference
Citations 
PageRank 
References 
0
0.34
13
Authors
4
Name
Order
Citations
PageRank
Tuan Anh Nguyen118319.18
Marco Aiello21019101.97
Takuro Yonezawa38422.34
Kenji Tei48411.24