713 research outputs found
HySIM: A Hybrid Spectrum and Information Market for TV White Space Networks
We propose a hybrid spectrum and information market for a database-assisted
TV white space network, where the geo-location database serves as both a
spectrum market platform and an information market platform. We study the
inter- actions among the database operator, the spectrum licensee, and
unlicensed users systematically, using a three-layer hierarchical model. In
Layer I, the database and the licensee negotiate the commission fee that the
licensee pays for using the spectrum market platform. In Layer II, the database
and the licensee compete for selling information or channels to unlicensed
users. In Layer III, unlicensed users determine whether they should buy the
exclusive usage right of licensed channels from the licensee, or the
information regarding unlicensed channels from the database. Analyzing such a
three-layer model is challenging due to the co-existence of both positive and
negative network externalities in the information market. We characterize how
the network externalities affect the equilibrium behaviours of all parties
involved. Our numerical results show that the proposed hybrid market can
improve the network profit up to 87%, compared with a pure information market.
Meanwhile, the achieved network profit is very close to the coordinated
benchmark solution (the gap is less than 4% in our simulation).Comment: This manuscript serves as the online technical report of the article
published in IEEE International Conference on Computer Communications
(INFOCOM), 201
Providing Long-Term Participation Incentive in Participatory Sensing
Providing an adequate long-term participation incentive is important for a
participatory sensing system to maintain enough number of active users
(sensors), so as to collect a sufficient number of data samples and support a
desired level of service quality. In this work, we consider the sensor
selection problem in a general time-dependent and location-aware participatory
sensing system, taking the long-term user participation incentive into explicit
consideration. We study the problem systematically under different information
scenarios, regarding both future information and current information
(realization). In particular, we propose a Lyapunov-based VCG auction policy
for the on-line sensor selection, which converges asymptotically to the optimal
off-line benchmark performance, even with no future information and under
(current) information asymmetry. Extensive numerical results show that our
proposed policy outperforms the state-of-art policies in the literature, in
terms of both user participation (e.g., reducing the user dropping probability
by 25% to 90%) and social performance (e.g., increasing the social welfare by
15% to 80%).Comment: This manuscript serves as the online technical report of the article
published in IEEE International Conference on Computer Communications
(INFOCOM), 201
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