Efficient Clustering Algorithms for Cell phone based Sensor Networks
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At the end of 2014 the number of cellular subscribers is about to cross 7 billion worldwide. The ubiquitous presence of cell phones makes them an ideal platform for carrying out sensing tasks for next generation wireless sensor networks. In this book, the authors present human mobility based clustering algorithms for sensor data routing of Cell phone based sensor networks. Algorithms are presented for two different sensor data routing applications, namely monitoring and moving event localization. Presented algorithms use two novel human walk context metrics and perform better compared to insta...
At the end of 2014 the number of cellular subscribers is about to cross 7 billion worldwide. The ubiquitous presence of cell phones makes them an ideal platform for carrying out sensing tasks for next generation wireless sensor networks. In this book, the authors present human mobility based clustering algorithms for sensor data routing of Cell phone based sensor networks. Algorithms are presented for two different sensor data routing applications, namely monitoring and moving event localization. Presented algorithms use two novel human walk context metrics and perform better compared to instantaneous mobility metric of traditional algorithms. Power law distributions of flight length and pause time, offers excellent opportunities for creating stable cluster structures. Presented human walk context metrics exploit Expectation paradox and Mass-count disparity properties of power law distribution of flight length and pause time. These opportunities arise for high density node distributions. This book presets extensive simulation results and it is anticipated that the presented approach will also be effective for mobility management of 4G-5G networks and D2D communications as well
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