Abraham / Falcon / Koeppen Computational Intelligence in Wireless Sensor Networks

Recent Advances and Future Challenges
1. Auflage 2017
ISBN: 978-3-319-47715-2
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 676, 210 Seiten, eBook

Reihe: Studies in Computational Intelligence

This book emphasizes the increasingly important role that Computational Intelligence (CI) methods are playing in solving a myriad of entangled Wireless Sensor Networks (WSN) related problems. The book serves as a guide for surveying several state-of-the-art WSN scenarios in which CI approaches have been employed. The reader finds in this book how CI has contributed to solve a wide range of challenging problems, ranging from balancing the cost and accuracy of heterogeneous sensor deployments to recovering from real-time sensor failures to detecting attacks launched by malicious sensor nodes and enacting CI-based security schemes. Network managers, industry experts, academicians and practitioners alike (mostly in computer engineering, computer science or applied mathematics) benefit from th e spectrum of successful applications reported in this book. Senior undergraduate or graduate students may discover in this book some problems well suited for their own research endeavors.

Zielgruppe

Research

Autoren/Hrsg.

Abraham, Ajith

Falcon, Rafael

Koeppen, Mario

Inhaltsverzeichnis

Preface.- A Genetic Programming Approach to Cost-Sensitive Control in Resource Constrained Sensor Systems.- A Study on Performance of the Hill Climbing Heuristic Method for Router Placement in Mesh Networks.- An Automated Irrigation System Based on a Low- Cost Micro-controller for Tomato Production in South India.- Artificial-Neural-Network-based Real-Time Urban Road Traffic State Estimation Framework.- Attack Detection using Evolutionary Computation.- Computational Intelligence based Security in WSNs - Technologies and Design Challenges.- Efficient Anomaly Detection System for Video Surveillance Application in WVSN with Particle Swarm Optimization.- Planning Robust Sensor Relocation Trajectories for a Mobile Robot with Evolutionary Multi-Objective Optimization.