Ambient Intelligence Context-Based Cross-Layer Design in Wireless Sensor Networks

Abstract

By exchanging information directly between non-adjacent protocol layers, cross-layer (CL) interaction can significantly improve and optimize network performances such as energy efficiency and delay. This is particularly important for wireless sensor networks (WSNs) where sensor devices are energy-constrained and deployed for real-time monitoring applications. Existing CL schemes mainly exploit information exchange between physical, medium access control (MAC), and routing layers, with only a handful involving application layer. For the first time, we proposed a framework for CL optimization based on user context of ambient intelligence (AmI) application and an ontology-based context modeling and reasoning mechanism. We applied the proposed framework to jointly optimize MAC and network (NET) layer protocols for WSNs. Extensive evaluations show that the resulting optimization through context awareness and CL interaction for both MAC and NET layer protocols can yield substantial improvements in terms of throughput, packet delivery, delay, and energy performances.

An interference-tolerant nitrate smart sensor for Wireless Sensor Network applications

“…More complex solutions yielded good results, but their high requirements of computing resources make them unsuitable for WSN. Instead, the proposed methodology brings together simplicity and highly satisfactory results[17].It assumes that there is some relationship between the concentration of interferents and the error committed in the determination. Bearing this in mind, several experiments were carried out using standard solutions; then, with the results obtained as well as the corresponding true values, different mathematical procedures were evaluated to determine the error committed.…”

A Multi-Protocol IoT Platform Based on Open-Source Frameworks

“…One way for delivering such capabilities is to use semantics. Many ontologies and data models have been proposed regarding the IoT domain for devices, data, and IoT resources in general, e.g., the IoT-Lite [21], which is tailored to sensor networks; the SAREF (Smart Appliances REFerence) ontology [22], which describes smart appliances and was defined by collaborating with the industrial sector; the Ontology for Wearables Data Interoperability [23], which can be used for ambient assisted living applications; and IoT-A [24]. Such semantic descriptions can help with the discoverability of devices and services and with their automated reconfigurability and management.…”

Non-Orthogonal Multiple Access for Ubiquitous Wireless Sensor Networks

“…In this case, NOMA can offer a practical solution by enabling direct DL transmissions from sink node to multiple sensors simultaneously. DL transmissions are initiated when sink node queries a specific sensor or group of sensors for some information [ 7 , 8 ], or communicates information essential for their operations such as sleep-wake schedules [ 9 ]. Further, unlike 5G, most UWSNs operate in unlicensed spectrum where sensors also experience cross-technology (CT) interferences [ 10 ] from other devices sharing the same spectrum.…”