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Compressed Sensing in Cyber Physical Social Systems

  • Radu GrosuEmail author
  • Elahe Ghalebi K.
  • Ali Movaghar
  • Hamidreza Mahyar
Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10760)

Abstract

We overview the main results in Compressed Sensing and Social Networks, and discuss the impact they have on Cyber Physical Social Systems (CPSS), which are currently emerging on top of the Internet of Things. Moreover, inspired by randomized Gossip Protocols, we introduce TopGossip, a new compressed-sensing algorithm for the prediction of the top-k most influential nodes in a social network. TopGossip is able to make this prediction by sampling only a relatively small portion of the social network, and without having any prior knowledge of the network structure itself, except for its set of nodes. Our experimental results on three well-known benchmarks, Facebook, Twitter, and Barabási, demonstrate both the efficiency and the accuracy of the TopGossip algorithm.

Notes

Acknowledgments

This work was partially supported by the following awards: AT-HRSM CPSS/IoT Ecosystem, NSF-Frontiers Cyber-Cardia, US-AFOSR Arrive, EU-Artemis EMC2, EU-Ecsel Semi40, EU-Ecsel Productive 4.0, AT-FWF-NFN RiSE, AT-FWF-LogicCS-DC, AT-FFG Harmonia, AT-FFG Em2Apps, and TUW-CPPS-DK.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Radu Grosu
    • 1
    Email author
  • Elahe Ghalebi K.
    • 1
  • Ali Movaghar
    • 2
  • Hamidreza Mahyar
    • 1
  1. 1.Fakultät für InformatikTechnische Universität WienViennaAustria
  2. 2.Department of Computer EngineeringSharif University of TechnologyTehranIran

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