human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "competition with dynamic spectrum leasing"
  Abstract: Dynamic spectrum leasing can greatly enhance the spectrum efficiency and encourage more flexible services in the spectrum market. This paper presents a detailed analytical study of the strategic interactions of two competing secondary network operators (duopoly) who need to make optimal investment (leasing) and pricing decisions while taking secondary endusers' heterogeneous wireless characteristics into consideration. The operators need to determine how much to lease from the spectrum owner, and compete to sell the spectrum to secondary users to maximize their individual profits. We model the system as a three-stage multi-leader dynamic game. Both the operators' equilibrium investment and pricing decisions turn out to have nice threshold properties. Each secondary user receives a fair equilibrium resource allocation that only depends on the leasing cost of the operators and is independent of other users' channel conditions and transmission powers. To further understand the impact of competition, we compare the duopoly equilibrium result with the coordinated case where the two operators cooperate to maximize the total profit. We show that the Price of Anarchy of the two operators' total profit is 82% with symmetric leasing costs, i.e., the maximum loss of the total profit due to competition is no larger than 18%. We also show that competition always leads to better payoffs for users compared with the coordinated case.

Connected through hyperedge HE-1 (induced by source paper "the value of side information in secondary spectrum markets"):
  with members:
    - "secondary spectrum market to acquire or not to acquire side information"
    - "quality sensitive price competition in spectrum oligopoly part ii"
    - "quality sensitive price competition in spectrum oligopoly"
    - "competition between wireless service providers pricing equilibrium and efficiency"

Connected through hyperedge HE-2 (induced by source paper "optimal bidding in repeated wireless spectrum auctions with budget constraints"):
  with members:
    - "budget optimization for sponsored search censored learning in mdps"
    - "secondary spectrum auctions for symmetric and submodular bidders"
    - "budget optimization in search based advertising auctions"

Connected through hyperedge HE-3 (induced by source paper "quality sensitive price competition in spectrum oligopoly part ii"):
  with members:
    - "quality sensitive price competition in spectrum oligopoly"

Connected through hyperedge HE-4 (induced by source paper "flexauc serving dynamic demands in a spectrum trading market with flexible auction"):
  with members:
    - "database assisted distributed spectrum sharing"

Connected through hyperedge HE-5 (induced by source paper "database assisted distributed spectrum sharing"):
  with members:
    - "joint distributed access point selection and power allocation in cognitive radio networks"
    - "quantifying the availability of tv white spaces for cognitive radio operation in the uk"

Connected through hyperedge HE-6 (induced by source paper "delay sensitive communications over cognitive radio networks"):
  with members:
    - "investment and pricing with spectrum uncertainty a cognitive operator s perspective"
    - "on myopic sensing for multi channel opportunistic access structure optimality and performance"

Connected through hyperedge HE-7 (induced by source paper "incentive mechanisms for hierarchical spectrum markets"):
  with members:
    - "efficiency loss in revenue optimal auctions"

Connected through hyperedge HE-8 (induced by source paper "competition and regulation in wireless services markets"):
  with members:
    - "let cognitive radios imitate imitation based spectrum access for cognitive radio networks"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.NI(Networking and Internet Architecture)