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: "to relay or not to relay learning device to device relaying strategies in cellular networks"
  Abstract: We consider a cellular network where mobile transceiver devices that are owned by self-interested users are incentivized to cooperate with each other using tokens, which they exchange electronically to "buy" and "sell" downlink relay services, thereby increasing the network's capacity compared to a network that only supports base station-to-device (B2D) communications. We investigate how an individual device in the network can learn its optimal cooperation policy online, which it uses to decide whether or not to provide downlink relay services for other devices in exchange for tokens. We propose a supervised learning algorithm that devices can deploy to learn their optimal cooperation strategies online given their experienced network environment. We then systematically evaluate the learning algorithm in various deployment scenarios. Our simulation results suggest that devices have the greatest incentive to cooperate when the network contains (i) many devices with high energy budgets for relaying, (ii) many highly mobile users (e.g., users in motor vehicles), and (iii) neither too few nor too many tokens. Additionally, within the token system, self-interested devices can effectively learn to cooperate online, and achieve over 20% higher throughput on average than with B2D communications alone, all while selfishly maximizing their own utilities.

Connected through hyperedge HE-1 (induced by source paper "big data meet cyber physical systems a panoramic survey"):
  with members:
    - "information and communications technologies for sustainable development goals state of the art needs and perspectives"
    - "improving the coverage and spectral efficiency of millimeter wave cellular networks using device to device relays"
    - "developing an edge computing platform for real time descriptive analytics"
    - "security and privacy aspects in mapreduce on clouds a survey"
    - "wireless device to device caching networks basic principles and system performance"
    - "social computing for mobile big data"
    - "streaming big data meets backpressure in distributed network computation"
    - "big data caching for networking moving from cloud to edge"

Connected through hyperedge HE-2 (induced by source paper "improving the coverage and spectral efficiency of millimeter wave cellular networks using device to device relays"):
  with members:
    - "modeling and analyzing millimeter wave cellular systems"
    - "optimal relay probing in millimeter wave cellular systems with device to device relaying"
    - "energy efficiency in relay assisted mmwave cellular networks"
    - "a survey of millimeter wave mmwave communications for 5g opportunities and challenges"
    - "connectivity of millimeter wave networks with multi hop relaying"
    - "coverage and rate analysis for millimeter wave cellular networks"
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "millimeter wave channel modeling and cellular capacity evaluation"

Connected through hyperedge HE-3 (induced by source paper "relay assisted device to device communication approaches and issues"):
  with members:
    - "distributed resource allocation for relay aided device to device communication under channel uncertainties a stable matching approach"
    - "distributed resource allocation for relay aided device to device communication a message passing approach"
    - "resource allocation under channel uncertainties for relay aided device to device communication underlaying lte a cellular networks"
    - "base station assisted device to device communications for high throughput wireless video networks"
    - "resource allocation for network integrated device to device communications using smart relays"

Connected through hyperedge HE-4 (induced by source paper "optimal time reuse in cooperative d2d relaying networks"):
  with members:
    - "interference constrained pricing for d2d networks"
    - "energy efficient cell activation user association and spectrum allocation in heterogeneous networks"
    - "coexistence of wi fi and heterogeneous small cell networks sharing unlicensed spectrum"

Connected through hyperedge HE-5 (induced by source paper "traffic aware transmission mode selection in d2d enabled cellular networks with token system"):
  with members:
    - "a survey on device to device communication in cellular networks"

Connected through hyperedge HE-6 (induced by source paper "designing security aware incentives for computation offloading via device to device communication"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "a survey on device to device communication in cellular networks"
    - "efficiency resource allocation for device to device underlay communication systems a reverse iterative combinatorial auction based approach"

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.GT(Computer Science and Game Theory)