Resource Allocation and Optimal Scheduling in Cognitive Wireless Sensor Networks – Mathematical Models

Dear Colleagues,

It is believed that wireless sensor networks (WSN), machine-type communications (MTC), cognitive radio networks (CRN), and several other technologies play major roles in IoT (the Internet of Things). IoT is expected to revolutionize how we do things in many ways. However, the effective and efficient design and deployment of such large-scale networks requires very effective and efficient resource allocation. Currently WSN is limited to ISM band (unlicensed channels) for data transmission.  This is quite limiting and does affect latency adversely. Recently, it is believed that cognitive technology can be utilized by WSN through sensing and monitoring the licensed channels and using them when free. This led to the idea of cognitive wireless sensor networks. While efficient allocation is key, how the allocated resources are scheduled also plays a significant role. It is believed that the deployment of 5G technologies in 2020 is imminent. These advancements will be welcomed, because they would increase network capacity and considerably improve latency: a key feature required for the success of IoT. However, optimal resource allocation and scheduling of transmission of data gathered is key to the realization of this vision. The data collected by the Wireless sensor networks can be transmitted over different types of channels: licensed or unlicensed. Managing how the data is distributed over these types of channels is key to improving latency, and this capitalizes on the cognitive wireless sensor networks technology. In the end, mathematical models that assist in optimal resource allocation and scheduling of WSN over the different types of channels are essential to the success of these technologies.

The aim of this Special Issue is to assemble mathematical tools and models for the implementation of resource allocation and scheduling for cognitive wireless sensor networks.

Potential topics include, but are not limited to:

• Optimization models for resource allocations for WSN.
• Optimization models for resource allocations for CRN.
• Understanding the complexity of the interworking of WSN, CRN in IoT
• Optimal use of both the licensed and unlicensed channels for WSN – resource allocation and scheduling.
• Exploring the features of 5G in cognitive wireless network operation.
• Energy-efficient resource allocation schemes for CRN.

Prof. Dr. Attahiru Alfa
Prof. Dr. B. T. Maharaj
Dr. Haitham Abu Ghazaleh
Guest Editors

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