CenSen: Smart Sensing for CloudIoT

CenSen: Smart Sensing for CloudIoT explores the design and development of a centralized sensor framework that integrates Wireless Sensor Networks (WSNs), cloud computing, and Internet of Things (IoT) technologies to enable scalable, secure, and energy-efficient smart systems. The book presents a comprehensive CloudIoT architecture that simplifies sensor management, improves real-time data processing, and enhances resource utilization across distributed environments. It addresses critical challenges such as load balancing, task scheduling, routing optimization, latency reduction, scalability, and energy consumption in cloud-enabled IoT ecosystems. The framework uses advanced hybrid metaheuristic algorithms, deep learning techniques, and intelligent scheduling models including F-COA, SA-RBM, SISP-WHO, Ch-KPA, R-EDF, and LC-GTO to optimize cluster head selection, workflow scheduling, virtual machine allocation, and dynamic resource management. Through simulation and performance analysis using CloudSim, the book demonstrates how CenSen improves execution time, response time, throughput, network lifetime, and cost efficiency compared to existing approaches.

Pages: 168, Paperback, LAP Lambert Academic Publishing