Knowledge Representation and Reasoning for the Design of Resilient Sensor Networks

• Published in: Intelligent Sensor Networks pp. 93 - 113
• Main Authors: Kelle, David, El-Mezyani, Touria, Srivastava, Sanjeev, Cartes, David
• Format: Book Chapter
• Language: English
• Published: CRC Press 2013
• Edition: 1
• Subjects: Faulty Sensor; Sensor Failures; IEEE-14 Bus System; Sensor Teams; Sensor Networks; Simplicial Complexes; Belief Parameter; Distributed Energy Resources; Detect Sensor Failures; Vice Versa; Wireless Sensor Networks; Path Algebra; Adjacency Matrix; Target Complex; Fault Events; Reasoning Algorithm; Redundancy Check; Distributed Kalman Filtering; Facet Chains; Cognitive Wireless Sensor Networks; Intelligent Sensor Networks; Basic Cognitive Structure; Broadband Power Lines
• ISBN: 1138199745; 9781439892817; 1439892814; 9781138199743
• DOI: 10.1201/b14300-6

This chapter proposes a new approach for the design of resilient sensor networks using a knowledge representation (KR) formalism that will facilitate reasoning and collaboration among sensors. The developed approach can be used to design resilient sensor networks that can assist the power management, control, and monitoring systems in inferring and predicting the system state, as well as determining the health of all components, including sensors. KR is the key to the design of an intelligent sensor management system because it provides the basic cognitive structure of reasoning and machine learning. The chapter provides an algebra for reasoning by analogy by defining a concept similar to a path called a facet chain. The development of technologies presents an opportunity to develop a new intelligent control paradigm based on reasoning by analogy with the goal of improving the capability of systems.