Hybrid model of inter-stage spectrum trading in multistage game-theoretic framework

Dynamic spectrum access（DSA）,consisting of spectrum sharing and spectrum trading stage,becomes a promising approach to increase the efficiency of spectrum usage and system performance.In this paper,from the perspective of individual interest optimization,we focus on strategy adaptation of network users and their interaction in spectrum trading process.Considering adverse effects on decision-making accuracy and the fairness among network users via local information acquirement,a hybrid game model based on global information of relevant spectrum is proposed to formulate intelligent behaviors of both primary and secondary users.Specifically,by using the evolutionary game theory,a spectrum-selection approach for the evolution process of secondary users is designed to converge to the evolutionary equilibrium gradually.Moreover,competition among primary users is modeled as a non-cooperative game and an iterative algorithm is employed to achieve the Nash equilibrium.The simulation results show that the proposed hybrid game model investigates network dynamics under different network parameter settings.

Cost-Minimized Virtual Elastic Optical Network Provisioning with Guaranteed QoS

Network virtualization is important for elastic optical networks(EONs)because of more flexible service provisioning.To ensure guaranteed quality of service(QoS)for each virtual elastic optical network(VEON),clients usually request network resources from a network operator based on their bandwidth requirements predicted from historical traffic demands.However,this may not be efficient as the actual traffic demands of users always fluctuate.To tackle this,we propose a new VEON service provisioning scheme,called SATP,which consists of three stages,i.e.,spectrum assignment(SA),spectrum trading(ST),and spectrum purchasing(SP).Unlike conventional once-for-all VEON service provisioning approaches,the SATP scheme first allocates spectrum resources to VEONs according to their predicted bandwidth requirements with a satisfaction ratio α(0<α≤1).Then,to minimize service degradation on VEONs which are short of assigned spectra for their peak traffic periods,the scheme allows VEONs to trade spectra with each other according to their actual bandwidth requirements.Finally,it allows VEON clients to purchase extra spectrum resources from a network operator if the spectrum resources are still insufficient.To optimize this entire process,we formulate the problem as a mixed integer linear programming(MILP)model and also develop efficient heuristic algorithms for each stage to handle large test scenarios.Simulations are conducted under different test conditions for both static and dynamic traffic demand scenarios.Results show that the proposed SATP scheme is efficient and can achieve significant performance improvement under both static and dynamic scenarios.