A Game Theoretical Incentive Scheme for Relay Selection Services in Mobile Social Networks

CreditCoin: A Privacy-Preserving Blockchain-Based Incentive Announcement Network for Communications of Smart Vehicles

“…The users are encouraged to forward and receive packets with the incentive to increase their coins. Existing work [42][43][44][45] has proved this mechanism is effective in crowdsourcing tasks and ad hoc networks. However, they are not suitable for the privacy-preserving requirements of vehicular announcement networks.…”

An evolutionary bargaining‐based approach for incentivized cooperation in opportunistic networks

“…Like many incentive‐based mechanisms such as Xu et al and Wang et al, we assume also that a node participating in messages forwarding is stimulated through some reward/payment and there is a virtual currency to organize the payments among nodes. All payment transactions are conducted through a Credit Clearance Center (CCC), which is accessible to the network nodes, eg, through the Internet . Each node has an account in the CCC, and each transaction should be processed by the CCC.…”

An adaptive resource allocation model in anti-money laundering system

“…Most of these approaches have been widely used for financial modeling which try to identify ML patterns by different techniques such as support vector machine [12], correlation analysis [13], neural network [14], etc. It is known that the Markov model is widely used in wireless communication [15][16][17][18] and cloud computing [19][20][21][22], but none of these works addressed AML resources allocation issue based on a reward model, considering prioritized suspicious transaction reports. In order to well capture the dynamic suspicious transaction reports arrivals and departures in the AML resource allocation domain, in this paper, we use Semi-Markov Decision Process (SMDP) which belongs to Markov model to set up our proposed Adaptive AML Resource Allocation Model (AAMLRAM).…”

“…From the reward function (18) and probability Eqs. 14, 15 and 16, the expected total discounted reward ν(s) at state s ∈ S is related with the arrival rates of HRO suspicious transaction report (λ h ) and L/MRO suspicious transaction report (λ l ), the mean processing rate for a suspicious transaction report of each allocation scheme ( μ ξ(c) ) , the occupied AML resource expressed by the number of being occupied AMLRAUs (s c * c) and K are fixed.…”