Citation
Waseem Abbas, Aron Laszka, Xenofon Koutsoukos. "Graph-Theoretic Approach for Increasing Participation in Social Sensing". 2nd International Workshop on Social Sensing (SocialSens 2017), April, 2017.

Abstract
Participatory sensing enables individuals, each with limited sensing capability, to share measurements and contribute towards developing a complete knowledge of their environment. Œe success of a participatory sensing application is o‰en measured in terms of the number of users participating. In most cases, an individual’s eagerness to participate depends on the group of users who already participate. For instance, when users share data with their peers in a social network, the engagement of an individual depends on its peers. Such engagement rules have been studied in the context of social networks using the concept of k-core, which assumes that participation is determined solely by network topology. However, in participatory sensing, engagement rules must also consider user heterogeneity, such as di‚erences in sensing capabilities and physical location. To account for heterogeneity, we introduce the concept of (r,s)-core to model the set of participating users. We formulate the problem of maximizing the size of the (r,s)-core using 1) anchor users, who are incentivized to participate regardless of their peers, and by 2) assigning capabilities to users. Since these problems are computationally challenging, we study heuristic algorithms for solving them. Based on real-world social networks as well as random graphs, we provide numerical results showing signi€cant improvement compared to random selection of anchor nodes and label assignments.

Electronic downloads

• http://aronlaszka.com/papers/abbas2017graph.pdf

• HTML

  Waseem Abbas, Aron Laszka, Xenofon Koutsoukos. <a
  href="http://www.cps-forces.org/pubs/244.html"
  >Graph-Theoretic Approach for Increasing Participation in
  Social Sensing</a>, 2nd International Workshop on
  Social Sensing (SocialSens 2017), April, 2017.

• Plain text

  Waseem Abbas, Aron Laszka, Xenofon Koutsoukos.
  "Graph-Theoretic Approach for Increasing Participation
  in Social Sensing". 2nd International Workshop on
  Social Sensing (SocialSens 2017), April, 2017.

• BibTeX

  @inproceedings{AbbasLaszkaKoutsoukos17_GraphTheoreticApproachForIncreasingParticipationInSocial,
      author = {Waseem Abbas and Aron Laszka and Xenofon Koutsoukos},
      title = {Graph-Theoretic Approach for Increasing
                Participation in Social Sensing},
      booktitle = {2nd International Workshop on Social Sensing
                (SocialSens 2017)},
      month = {April},
      year = {2017},
      abstract = {Participatory sensing enables individuals, each
                with limited sensing capability, to share
                measurements and contribute towards developing a
                complete knowledge of their environment. ÂŒe
                success of a participatory sensing application is
                o‰en measured in terms of the number of users
                participating. In most cases, an individual’s
                eagerness to participate depends on the group of
                users who already participate. For instance, when
                users share data with their peers in a social
                network, the engagement of an individual depends
                on its peers. Such engagement rules have been
                studied in the context of social networks using
                the concept of k-core, which assumes that
                participation is determined solely by network
                topology. However, in participatory sensing,
                engagement rules must also consider user
                heterogeneity, such as di‚erences in sensing
                capabilities and physical location. To account for
                heterogeneity, we introduce the concept of
                (r,s)-core to model the set of participating
                users. We formulate the problem of maximizing the
                size of the (r,s)-core using 1) anchor users, who
                are incentivized to participate regardless of
                their peers, and by 2) assigning capabilities to
                users. Since these problems are computationally
                challenging, we study heuristic algorithms for
                solving them. Based on real-world social networks
                as well as random graphs, we provide numerical
                results showing signi€cant improvement compared
                to random selection of anchor nodes and label
                assignments. },
      URL = {http://cps-forces.org/pubs/244.html}
  }
  

Posted by Waseem Abbas on 2 Mar 2017.
Groups: forces
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