Design of Clustering Techniques in Cognitive Radio Sensor Networks

In recent decades, several optimization algorithms have been developed for selecting the most energy efficient clusters in order to save power during transmission to a shorter distance while restricting the Primary Users (PUs) interference. The Cognitive Radio (CR) system is based on the Adaptive Swarm Distributed Intelligent based Clustering algorithm (ASDIC) that shows better spectrum sensing among group of multiusers in terms of sensing error, power saving, and convergence time. In this research paper, the proposed ASDIC algorithm develops better energy efficient distributed cluster based sensing with the optimal number of clusters on their connectivity. In this research, multiple random Secondary Users (SUs), and PUs are considered for implementation. Hence, the proposed ASDIC algorithm improved the convergence speed by combining the multi-users clustered communication compared to the existing optimization algorithms. Experimental results showed that the proposed ASDIC algorithm reduced the node power of 9.646% compared to the existing algorithms. Similarly, ASDIC algorithm reduced 24.23% of SUs average node power compared to the existing algorithms. Probability of detection is higher by reducing the Signal-to-Noise Ratio (SNR) to 2 dB values. The proposed ASDIC delivers low false alarm rate compared to other existing optimization algorithms in the primary detection. Simulation results showed that the proposed ASDIC algorithm effectively solves the multimodal optimization problems and maximizes the performance of network capacity.     

A case study for the evaluation of realistic energy retrofit strategies for public office buildings in the Southern Hemisphere

The building sector offers significant opportunities for reducing the energy consumption with considerable economic, environmental and health benefits. Governments can lead the way by retrofitting existing public buildings to reinforce their commitment to improve energy efficiency. Similar design standards, end-uses and operational profiles are usually established for public buildings based on the services they offer. Retrofitting a public building can therefore serve as an ideal test-bed for energy efficiency measures for other buildings within a particular service category. This study first analysed the current electricity consumption of a public office building in Mauritius, located in the Southern Hemisphere. A complete model of the building was created, validated and then simulated to investigate the impact of realistic retrofit strategies on the electricity consumption. Results showed that lighting retrofit achieved the most significant reduction while measures that improved the thermal envelope of the building resulted in smaller energy savings. The possibility of exploiting solar energy was explored by simulating a 70 kW_p photovoltaic system installed on the roof. An equivalent of 8.5% of the annual electricity consumption of the building could thus be generated. A financial analysis is also presented for all retrofit scenarios in terms of annual return and payback period.