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: "how to price fresh data"
  Abstract: We introduce the concept of a fresh data market, in which a destination user requests, and pays for, fresh data updates from a source provider. Data freshness is captured by the {\it age of information} (AoI) metric, defined as the time elapsed since the latest update has reached the destination. The source incurs an operational cost, modeled as an increasing convex function of the number of updates. The destination incurs an age-related cost, modeled as an increasing convex function of the AoI. The source charges the destination for each update and designs a pricing mechanism to maximize its profit; the destination on the other hand chooses a data update schedule to minimize the summation of its payments to the source and its age-related cost. The interaction among the source and destination is hence game-theoretic. Motivated by the existing pricing literature, we first study a time-dependent pricing scheme, in which the price for each update depends on when it is requested. We show in this case that the game equilibrium leads to only one data update, which does not yield the maximum profit to the source. This motivates us to consider a quantity-based pricing scheme, in which the price of each update depends on how many updates have been previously requested. We show that among all pricing schemes in which the price of an update may vary according to both time and quantity, the quantity-based pricing scheme performs best: it maximizes the source's profit and minimizes the social cost of the system, defined as the aggregate source's operational cost and the destination's age-related cost. Numerical results show that the optimal quantity-based pricing can be 27% more profitable for the source and incurs 54% less social cost, compared with the optimal time-dependent pricing.

Connected through hyperedge HE-1 (induced by source paper "timely cloud computing preemption and waiting"):
  with members:
    - "sampling for remote estimation through queues age of information and beyond"
    - "on timely channel coding with hybrid arq"
    - "reducing age of information for computation intensive messages via packet replacement"
    - "on peak age of information in data preprocessing enabled iot networks"
    - "minimizing age of information with soft updates"
    - "status updates in a multi stream m g 1 1 preemptive queue"
    - "optimizing information freshness in wireless networks under general interference constraints"
    - "when to preempt age of information minimization under link capacity constraint"

Connected through hyperedge HE-2 (induced by source paper "regulating competition in age of information under network externalities"):
  with members:
    - "economics of age of information management under network externalities"
    - "dynamic pricing for controlling age of information"
    - "scalable mobile crowdsensing via peer to peer data sharing"
    - "age optimal information updates in multihop networks"
    - "minimizing the age of the information through queues"
    - "update or wait how to keep your data fresh"
    - "dynamic routing for social information sharing"
    - "the age of information real time status updating by multiple sources"

Connected through hyperedge HE-3 (induced by source paper "economics of age of information management under network externalities"):
  with members:
    - "dynamic pricing for controlling age of information"
    - "age optimal information updates in multihop networks"
    - "update or wait how to keep your data fresh"
    - "optimizing data freshness throughput and delay in multi server information update systems"
    - "on the age of information in status update systems with packet management"
    - "motivating smartphone collaboration in data acquisition and distributed computing"
    - "attack prevention for collaborative spectrum sensing in cognitive radio networks"

Connected through hyperedge HE-4 (induced by source paper "dynamic pricing for controlling age of information"):
  with members:
    - "economics of age of information management under network externalities"
    - "update or wait how to keep your data fresh"
    - "motivating smartphone collaboration in data acquisition and distributed computing"

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)