Social-Aware Data Diffusion in Delay Tolerant MANETs

  • Yang Zhang
  • Wei Gao
  • Guohong Cao
  • Tom La Porta
  • Bhaskar Krishnamachari
  • Arun Iyengar
Part of the Springer Optimization and Its Applications book series (SOIA, volume 58)


Most existing mobility-assisted data access techniques in delay tolerant mobile ad hoc networks (DT-MANETs) are designed to disseminate data to one or several particular destinations. Different from these works, we study the data diffusion problem which diffuses data among all moving nodes so that the nodes that are interested in this data item can get it easily either from their encountered friend nodes or stranger nodes. To reduce the data access delay, we introduce four social-aware data diffusion schemes based on the social relationship and data similarity of the contacts. We also provide solutions to quantify data/interest similarity and to determine whether two nodes are friends or strangers. Theoretical models are developed to analyze the data diffusion process and compare the performance of the four proposed diffusion schemes in terms of diffusion speed and query delay. We use real traces of human contacts to emulate data diffusion under different schemes. Both theoretical analysis and experimental results imply an interesting fact: to achieve better diffusion performance, each node should first diffuse the data similar to their common interests when it meets a friend, and first diffuse the data different to their common interests when it meets a stranger.


Interested Node Data Item Data Diffusion Delay Tolerant Network Infected Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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This work was supported in part by Network Science CTA under Grant W911NF-09-2-0053.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Yang Zhang
    • 1
  • Wei Gao
    • 1
  • Guohong Cao
    • 1
  • Tom La Porta
    • 1
  • Bhaskar Krishnamachari
    • 2
  • Arun Iyengar
    • 3
  1. 1.Department of Computer Science and EngineeringThe Pennsylvania State UniversityUniversity ParkUSA
  2. 2.Department of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesUSA
  3. 3.IBM T.J. Watson Research CenterHawthorneUSA

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