An epidemic game between contents in a wireless network

Abstract

Abstract-Consider a town with N competing sources of content where each one wishes to disseminate its own content and thus to make its content available to as many destination users as possible. A content here may stand for information about somoe cultural event or the list of hotels in town or the wheather report. The dissemination to the potential destination is done through a fleet of M mobile relays. The rate of dissemination of content of a given source to its potential destinations depends on how many relays have a copy of the content. We therefore focus on the problem of competition over the access to relays. Each source has to trade between the access costs and and the availability of his content in the relays. As access cost we consider here the transmission power used by the source. The power used determines the coverage of the transmission and thus the probability of reaching some relay. We model the competition using stochastic game approaches and then obtain the structure of the equilibrium strategies.

Game-Theoretic Frameworks for Epidemic Spreading and Human Decision-Making: A Review

“…] is not necessarily true, the N -intertwined deterministic model (4) serves as an approximation of the stochastic network model (7). Indeed, it is shown that the expected values p i in (4) are upper bounds on the actual probabilities given by ( 7) [22,97,102,134].…”

“…Indeed, it is shown that the expected values p i in (4) are upper bounds on the actual probabilities given by ( 7) [22,97,102,134]. Furthermore, [133] investigates how accurate the deterministic approximations (4) are in describing the stochastic model (7).…”

“…Apart from models that are based on Markov processes and ODEs, there are epidemic models based on stochastic differential equations [5,46], purely data-driven approaches [26], or spatial modeling [63,111,116,132]. Even though the focus of this review is on actual virus epidemics, there has been an abundant number of papers studying the spread of malware, Trojans, worms on mobile wireless networks [7,9,74], social networks [8,88,95], Delay Tolerant Networks [4,100], general computer network [80]. These papers introduced many useful techniques and insightful results applied to analyzing models of actual epidemics [7,74,80].…”

“…Even though the focus of this review is on actual virus epidemics, there has been an abundant number of papers studying the spread of malware, Trojans, worms on mobile wireless networks [7,9,74], social networks [8,88,95], Delay Tolerant Networks [4,100], general computer network [80]. These papers introduced many useful techniques and insightful results applied to analyzing models of actual epidemics [7,74,80]. In this review, we will introduce several papers that do not necessarily focus on actual epidemics but provide useful insights for models of actual epidemics [66,70,73,129,130,148].…”

Dissemination and competition between contents in lossy Susceptible Infected Susceptible (SIS) social networks

“…Content dissemination in social networks has been extensively studied, especially in the context of marketing, as surveyed in [13] and papers cited therein, or yet the more recent publication [12]. Several game theoretic approaches have been proposed to model competition in dissemination between contents, be they in wireless networks composed of sources and relays [2] or in the context of social networks where competition is on popularity and advertisement spaces such as in [3], [4].…”