Modeling and Optimization for Mobile Social Networks
1st Edition
Published on 25. November 2016
XII, 119 pages
978-3-319-47922-4 (ISBN)
Description
This book investigates the modeling and optimization issues in mobile social networks (MSNs). Firstly, the architecture and applications of MSNs are examined. The existing works on MSNs are reviewed by specifying the critical challenges and research issues. Then, with the introduction of MSN-based social graph and information dissemination mechanisms, the analytical model for epidemic information dissemination with opportunistic Links in MSNs is discussed. In addition, optimal resource allocation is studied based on a heterogeneous architecture, which provides mobile social services with high capacity and low latency. Finally, this book summarize some open problems and future research directions in MSNs.
Written for researchers and academics, this book is useful for anyone working on mobile networks, network architecture, or content delivery. It is also valuable for advanced-level students of computer science.
Written for researchers and academics, this book is useful for anyone working on mobile networks, network architecture, or content delivery. It is also valuable for advanced-level students of computer science.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XII, 119 p. 41 illus.
File size
4,64 MB
ISBN-13
978-3-319-47922-4 (9783319479224)
DOI
10.1007/978-3-319-47922-4
Schweitzer Classification
Other editions
Additional editions
Zhou Su | Qichao Xu | Kuan Zhang
Modeling and Optimization for Mobile Social Networks
Book
12/2016
Springer
€106.99
Shipment within 10-15 days
Content
Introduction.- Modeling of Epidemic Information Dissemination for MSNs.- Modeling of Selfishness-aware Incentive for MSNs.- Optimal Relay Services for MSNs.- Optimal Resource Allocation for MSNs.- Optimization of Network Architecture for MSNs.- Conclusions and Future Directions.
