Computational Intelligence in Wireless Sensor Networks : Recent Advances and Future Challenges (Studies in Computational Intelligence)

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Computational Intelligence in Wireless Sensor Networks : Recent Advances and Future Challenges (Studies in Computational Intelligence)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 210 p.
  • 言語 ENG
  • 商品コード 9783319838045
  • DDC分類 006.3

Full Description

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.

Contents

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.

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