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: "network formation games among relay stations in next generation wireless networks"
  Abstract: The introduction of relay station (RS) nodes is a key feature in next generation wireless networks such as 3GPP's long term evolution advanced (LTE-Advanced), or the forthcoming IEEE 802.16j WiMAX standard. This paper presents, using game theory, a novel approach for the formation of the tree architecture that connects the RSs and their serving base station in the uplink of the next generation wireless multi-hop systems. Unlike existing literature which mainly focused on performance analysis, we propose a distributed algorithm for studying the structure and dynamics of the network. We formulate a network formation game among the RSs whereby each RS aims to maximize a cross-layer utility function that takes into account the benefit from cooperative transmission, in terms of reduced bit error rate, and the costs in terms of the delay due to multi-hop transmission. For forming the tree structure, a distributed myopic algorithm is devised. Using the proposed algorithm, each RS can individually select the path that connects it to the BS through other RSs while optimizing its utility. We show the convergence of the algorithm into a Nash tree network, and we study how the RSs can adapt the network's topology to environmental changes such as mobility or the deployment of new mobile stations. Simulation results show that the proposed algorithm presents significant gains in terms of average utility per mobile station which is at least 17.1% better relatively to the case with no RSs and reaches up to 40.3% improvement compared to a nearest neighbor algorithm (for a network with 10 RSs). The results also show that the average number of hops does not exceed 3 even for a network with up to 25 RSs.

Connected through hyperedge HE-1 (induced by source paper "an online optimization framework for distributed fog network formation with minimal latency"):
  with members:
    - "proactive edge computing in latency constrained fog networks"
    - "an online secretary framework for fog network formation with minimal latency"
    - "enorm a framework for edge node resource management"
    - "joint subcarrier and cpu time allocation for mobile edge computing"
    - "fog computing based radio access networks issues and challenges"
    - "learning how to communicate in the internet of things finite resources and heterogeneity"
    - "challenges and opportunities in edge computing"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"

Connected through hyperedge HE-2 (induced by source paper "network formation in the sky unmanned aerial vehicles for multi hop wireless backhauling"):
  with members:
    - "inter operator resource management for millimeter wave multi hop backhaul networks"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"
    - "fso based vertical backhaul fronthaul framework for 5g wireless networks"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"
    - "matching theory for backhaul management in small cell networks with mmwave capabilities"

Connected through hyperedge HE-3 (induced by source paper "a game theoretic model for analysis and design of self organization mechanisms in iot"):
  with members:
    - "strategic formation of heterogeneous networks"
    - "formation games of reliable networks"
    - "internet of things applications and challenges in technology and standardization"

Connected through hyperedge HE-4 (induced by source paper "the game theoretic formation of interconnections between networks"):
  with members:
    - "the strategic formation of multi layer networks"
    - "robustness and algebraic connectivity of random interdependent networks"
    - "opinion dynamics in social networks a local interaction game with stubborn agents"
    - "worm epidemics in wireless ad hoc networks"

Connected through hyperedge HE-5 (induced by source paper "multihop relaying in millimeter wave networks a proportionally fair cooperative network formation game"):
  with members:
    - "coalition formation game for cooperative cognitive radio using gibbs sampling"
    - "coverage and rate analysis for millimeter wave cellular networks"
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "millimeter wave beamforming for wireless backhaul and access in small cell networks"

Connected through hyperedge HE-6 (induced by source paper "the strategic formation of multi layer networks"):
  with members:
    - "multilevel network games"

Connected through hyperedge HE-7 (induced by source paper "coalitional graph games for popular content distribution in cognitive radio vanets"):
  with members:
    - "coalitional games in partition form for joint spectrum sensing and access in cognitive radio networks"
    - "coalitional game theory for communication networks a tutorial"
    - "a game theoretic framework for incentives in p2p systems"

Connected through hyperedge HE-8 (induced by source paper "repeated games for inter operator spectrum sharing"):
  with members:
    - "a game theoretic view of the interference channel impact of coordination and bargaining"
    - "cooperative game theory and the gaussian interference channel"

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.IT(Information Theory)