Cognitive Sensors and IoT: Architecture, Deployment, and Data Delivery

Description

Features Presents the Cognitive Information Centric Sensor Network (CICSN) framework for the IoT Discusses the most appropriate deployment strategy for these cognitive nodes under realistic assumptions that cares about the Quality of Information (QoI) Uses a Quality of Information (QoI) aware data delivery strategy, with Analytic Hierarchy Process (AHP) as the reasoning technique, to identify data delivery paths that dynamically adapt to changing network conditions and user requirements Explores heuristic learning techniques to improve the success rate of data delivery and hit ratio which applying in-network caching Summary This book presents the Cognitive Information Centric Sensor Network (CICSN) framework for the IoT. This framework is built on top of cognitive nodes, capable of knowledge representation, learning, and reasoning, along with an information-centric approach for data delivery. It also discusses the most appropriate deployment strategy for these cognitive nodes under realistic assumptions that cares about the Quality of Information (QoI). In addition, it uses a QoI aware data delivery strategy, with Analytic Hierarchy Process (AHP) as the reasoning technique to identify data delivery paths that dynamically adapt to changing network conditions and user requirements. ContentsChapter 1: Introduction to Cognition in IoT * Chapter 2: Information-Centric Sensor Networks for Cognitive IoT - An Overview *Chapter 3: Cognitive-Node Architecture and a Deployment Strategy for the Future Sensor Networks *Chapter 4: Quantifying Connectivity in Wireless Sensor Networks with Grid-based Deployments *Chapter 5: A Data Delivery Framework for Cognitive Information-Centric Sensor Networks in Smart Outdoor Monitoring *Chapter 6: Cognitive Routing Protocol for Disaster-inspired WSNs in the Internet of Things *Chapter 7: ARA - Adaptive Routing Approach for Heterogeneous & Pervasive IoT *Chapter 8: Fog-based Caching & Learning for Information-Centric Networks *Chapter 9: Conclusions and Future Directions *