Optimized Hexagon-Based Deployment for Large-Scale Ubiquitous Sensor Networks
Ubiquitous Sensor Networks (USNs) are a class of context-aware communication networks that provide an infrastructure for knowledge-based intelligent information service to anyone, anywhere, and at any time. To improve the capabilities of the network that delivers data to a cloud, this chapter proposes the use of Cognitive Nodes (CNs) based on the elements of learning, reasoning, and knowledge representation for USN applications. CNs provides enhanced capabilities to the wireless sensor networks (WSNs) to not only deal with the network connectivity and node dynamics in large-scale deployments but also to provide local storage before reaching the final destination on the cloud. Nodes in WSNs can be deployed in a flat, hierarchical, or geographic location-based strategy. In terms of energy conservation, hierarchical deployment strategies provide better performance for WSNs. Cognitive Nodes (CNs), Relay Nodes (RNs), Sensor Nodes (SNs) and a sink node are the node level entities of the network.