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Complex Patterns of Failure: Fault Tolerance via Complex Event Processing for IoT Systems

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Published
Publication date21/10/2019
Host publicationProceedings - 2019 IEEE International Congress on Cybermatics: 12th IEEE International Conference on Internet of Things, 15th IEEE International Conference on Green Computing and Communications, 12th IEEE International Conference on Cyber, Physical and Social Computing and 5th IEEE International Conference on Smart Data, iThings/GreenCom/CPSCom/SmartData 2019
PublisherIEEE
Pages986-993
Number of pages8
ISBN (electronic)9781728129808
<mark>Original language</mark>English
Event2019 IEEE International Conference on Internet of Things (iThings-2019) - Atlanta, United States
Duration: 14/07/201917/07/2019
http://cse.stfx.ca/~cybermatics/2019/ithings/index.php

Conference

Conference2019 IEEE International Conference on Internet of Things (iThings-2019)
Abbreviated titleiThings 2019
Country/TerritoryUnited States
CityAtlanta
Period14/07/1917/07/19
Internet address

Conference

Conference2019 IEEE International Conference on Internet of Things (iThings-2019)
Abbreviated titleiThings 2019
Country/TerritoryUnited States
CityAtlanta
Period14/07/1917/07/19
Internet address

Abstract

Fault-tolerance (FT) support is a key challenge for ensuring dependable Internet of Things (IoT) systems. Many existing FT-support mechanisms for IoT are static, tightly coupled, and inflexible, and so they struggle to provide effective support for dynamic IoT environments. This paper proposes Complex Patterns of Failure (CPoF), an approach to providing FT support for IoT systems using Complex Event Processing (CEP) that promotes modularity and reusability in FT-support design. System defects are defined using our Vulnerabilities, Faults, and Failures (VFF) framework, and error-detection strategies are defined as nondeterministic finite automata (NFA) implemented via CEP systems. We evaluated CPoF on an automated agriculture system and demonstrated its effectiveness against three types of error-detection checks: reasonableness, timing, and reversal. Using CPoF, we identified unreasonable environmental conditions and performance degradation via sensor data analysis.