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: "pricing and resource allocation via game theory for a small cell video caching system"
  Abstract: Evidence indicates that downloading on-demand videos accounts for a dramatic increase in data traffic over cellular networks. Caching popular videos in the storage of small-cell base stations (SBS), namely, small-cell caching, is an efficient technology for reducing the transmission latency while mitigating the redundant transmissions of popular videos over back-haul channels. In this paper, we consider a commercialized small-cell caching system consisting of a network service provider (NSP), several video retailers (VRs), and mobile users (MUs). The NSP leases its SBSs to the VRs for the purpose of making profits, and the VRs, after storing popular videos in the rented SBSs, can provide faster local video transmissions to the MUs, thereby gaining more profits. We conceive this system within the framework of Stackelberg game by treating the SBSs as specific types of resources. We first model the MUs and SBSs as two independent Poisson point processes, and develop, via stochastic geometry theory, the probability of the specific event that an MU obtains the video of its choice directly from the memory of an SBS. Then, based on the probability derived, we formulate a Stackelberg game to jointly maximize the average profit of both the NSP and the VRs. In addition, we investigate the Stackelberg equilibrium by solving a non-convex optimization problem. With the aid of this game theoretic framework, we shed light on the relationship between four important factors: the optimal pricing of leasing an SBS, the SBSs allocation among the VRs, the storage size of the SBSs, and the popularity distribution of the VRs. Monte Carlo simulations show that our stochastic geometry-based analytical results closely match the empirical ones. Numerical results are also provided for quantifying the proposed game-theoretic framework by showing its efficiency on pricing and resource allocation.

Connected through hyperedge HE-1 (induced by source paper "a crowdsourcing framework for on device federated learning"):
  with members:
    - "distributed federated learning for ultra reliable low latency vehicular communications"
    - "federated learning over wireless networks convergence analysis and resource allocation"
    - "on device federated learning via blockchain and its latency analysis"
    - "federated learning strategies for improving communication efficiency"
    - "online job scheduling in distributed machine learning clusters"
    - "federated optimization for heterogeneous networks"
    - "adaptive communication strategies to achieve the best error runtime trade off in local update sgd"
    - "beyond inferring class representatives user level privacy leakage from federated learning"

Connected through hyperedge HE-2 (induced by source paper "a personalized preference learning framework for caching in mobile networks"):
  with members:
    - "caching at base stations with heterogeneous user demands and spatial locality"
    - "user preference learning based edge caching for fog radio access network"
    - "on the effects of subpacketization in content centric mobile networks"
    - "how to cache in mobile hybrid iot networks"
    - "caching policy for cache enabled d2d communications by learning user preference"
    - "information theoretic caching the multi user case"
    - "caching incentive design in wireless d2d networks a stackelberg game approach"
    - "a learning based approach to caching in heterogenous small cell networks"

Connected through hyperedge HE-3 (induced by source paper "user association and path planning for uav aided mobile edge computing with energy restriction"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "joint trajectory and communication design for uav enabled multiple access"

Connected through hyperedge HE-4 (induced by source paper "the economics of video websites with membership advertising mode in wireless networks"):
  with members:
    - "auction based coopetition between lte unlicensed and wi fi"
    - "joint caching and pricing strategies for popular content in information centric networks"
    - "motivating smartphone collaboration in data acquisition and distributed computing"
    - "what will 5g be"
    - "five disruptive technology directions for 5g"
    - "price based resource allocation for spectrum sharing femtocell networks a stackelberg game approach"
    - "price differentiation for communication networks"

Connected through hyperedge HE-5 (induced by source paper "edge caching in delay constrained virtualized cellular networks analysis and market"):
  with members:
    - "inter operator infrastructure sharing trade offs and market"
    - "infrastructure sharing for mobile network operators analysis of trade offs and market"
    - "caching incentive design in wireless d2d networks a stackelberg game approach"
    - "a stackelberg game for incentive proactive caching mechanisms in wireless networks"
    - "virtualization of 5g cellular networks as a hierarchical combinatorial auction"
    - "integral approximations for coverage probability"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-6 (induced by source paper "a survey on mobile edge networks convergence of computing caching and communications"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "delay optimal computation task scheduling for mobile edge computing systems"
    - "caching at the wireless edge design aspects challenges and future directions"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "energy efficient resource allocation for mobile edge computation offloading extended version"
    - "wireless caching technical misconceptions and business barriers"
    - "cooperative device to device communications with caching"
    - "modeling and analysis for cache enabled networks with dynamic traffic"

Connected through hyperedge HE-7 (induced by source paper "mobile edge caching an optimal auction approach"):
  with members:
    - "fundamental tradeoff between storage and latency in cache aided wireless interference networks"
    - "how much cache is needed to achieve linear capacity scaling in backhaul limited dense wireless networks"
    - "information theoretic caching the multi user case"
    - "caching at the wireless edge design aspects challenges and future directions"
    - "joint caching and pricing strategies for popular content in information centric networks"
    - "wireless content caching for small cell and d2d networks"
    - "a rate distortion approach to caching"
    - "adaptive caching networks with optimality guarantees"

Connected through hyperedge HE-8 (induced by source paper "a content based centrality metric for collaborative caching in information centric fogs"):
  with members:
    - "a learning based approach to caching in heterogenous small cell networks"
    - "fundamental limits on throughput capacity in information centric networks"
    - "many to many matching games for proactive social caching in wireless small cell 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.IT(Information Theory)