Skip to content
Open global navigation

Cambridge University Press

AcademicLocation selectorSearch toggleMain navigation toggle
Cart

Your Cart

×

You have 0 items in your cart.

Register Sign in Wishlist

Behavior Dynamics in Media-Sharing Social Networks

$149.99 (C)

  • Date Published: May 2011
  • availability: In stock
  • format: Hardback
  • isbn: 9780521197274

$149.99 (C)
Hardback

Add to cart Add to wishlist

Other available formats:
eBook


Looking for an examination copy?

If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact collegesales@cambridge.org providing details of the course you are teaching.

Description
Product filter button
Description
Contents
Resources
Courses
About the Authors
  • In large-scale media-sharing social networks, where millions of users create, share, link and reuse media content, there are clear challenges in protecting content security and intellectual property, and in designing scalable and reliable networks capable of handling high levels of traffic. This comprehensive resource demonstrates how game theory can be used to model user dynamics and optimize design of media-sharing networks. It reviews the fundamental methodologies used to model and analyze human behavior, using examples from real-world multimedia social networks. With a thorough investigation of the impact of human factors on multimedia system design, this accessible book shows how an understanding of human behavior can be used to improve system performance. Bringing together mathematical tools and engineering concepts with ideas from sociology and human behavior analysis, this one-stop guide will enable researchers to explore this emerging field further and ultimately design media-sharing systems with more efficient, secure and personalized services.

    • Unique emphasis on the signal processing perspective of behavior modeling and analysis
    • Presents state-of-the-art concepts and recent results
    • Uses two real-world multimedia social networks as examples to demonstrate the methodologies used to model and analyze human behavior
    Read more

    Reviews & endorsements

    "In “Behavior Dynamics…”, the authors provide mathematical means for analysis of socially-enabled media sharing networks and their performance...one may find a good inspiration in the book." - IEEE Communications Magazine, June 2012

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity

    ×

    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?

    ×

    Product details

    • Date Published: May 2011
    • format: Hardback
    • isbn: 9780521197274
    • length: 350 pages
    • dimensions: 254 x 178 x 21 mm
    • weight: 0.84kg
    • contains: 110 b/w illus. 7 tables
    • availability: In stock
  • Table of Contents

    Preface
    Part I. Introduction:
    1. Introduction to media-sharing social networks
    2. Overview of multimedia fingerprinting
    3. Overview of mesh-pull peer-to-peer video streaming
    4. Game theory for social networks
    Part II. Behavior Forensics in Media-Sharing Social Networks:
    5. Equal-risk fairness in colluder social networks
    6. Leveraging side information in colluder social networks
    7. Risk-distortion analysis of multiuser collusion
    Part III. Fairness and Cooperation Stimulation:
    8. Game-theoretic modelling of colluder social networks
    9. Cooperation stimulation in peer-to-peer video streaming
    10. Optimal pricing for mobile video streaming
    Part IV. Misbehaving User Identification:
    11. Cheating behavior in colluder social networks
    12. Attack resistance in peer-to-peer video streaming
    13. Misbehavior detection in colluder social networks with different structures
    14. Structuring cooperation for hybrid peer-to-peer streaming
    References
    Index.

  • Authors

    H. Vicky Zhao, University of Alberta
    H. Vicky Zhao is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Alberta. The recipient of the IEEE Signal Processing Society Young Author Best Paper Award 2008, she is an Associate Editor for the IEEE Signal Processing Letters and the Journal of Visual Communication and Image Representation.

    W. Sabrina Lin, University of Maryland, College Park
    W. Sabrina Lin is a Research Associate in the Department of Electrical and Computer Engineering at the University of Maryland. She received the University of Maryland Future Faculty Fellowship in 2007.

    K. J. Ray Liu, University of Maryland, College Park
    K. J. Ray Liu is a Distinguished Scholar-Teacher of the University of Maryland. He received the IEEE Signal Processing Society Technical Achievement Award in 2009, and was Editor-in-Chief of the IEEE Signal Processing Magazine and the founding Editor-in-Chief of the EURASIP Journal on Advances in Signal Processing.

Sign In

Please sign in to access your account

Cancel

Not already registered? Create an account now. ×

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email cflack@cambridge.org

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website, your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Find content that relates to you

Back to top

Are you sure you want to delete your account?

This cannot be undone.

Cancel Delete

Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

×
Please fill in the required fields in your feedback submission.
×