Mobile Ad Hoc Networks : Current Status and Future Trends by Jonathan Loo
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Author: Jonathan Loo
Page Count: 538 pages
Published Date: 16 Dec 2011
Publisher: Taylor & Francis Inc
Publication Country: Bosa Roca, United States
Language: English
ISBN: 9781439856505
Download Link: Mobile Ad Hoc Networks Current Status and Future Trends
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Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service.
Also suitable as a text for graduate students, the book is organized into three sections: *Fundamentals of MANET Modeling and Simulation-Describes how MANETs operate and perform through simulations and models *Communication Protocols of MANETs-Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility *Future Networks Inspired By MANETs-Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms.
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