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: "on the complexity of the minimum latency scheduling problem on the euclidean plane"
  Abstract: We show NP-hardness of the minimum latency scheduling (MLS) problem under the physical model of wireless networking. In this model a transmission is received successfully if the Signal to Interference-plus-Noise Ratio (SINR), is above a given threshold. In the minimum latency scheduling problem, the goal is to assign a time slot and power level to each transmission, so that all the messages are received successfully, and the number of distinct times slots is minimized. #R##N#Despite its seeming simplicity and several previous hardness results for various settings of the minimum latency scheduling problem, it has remained an open question whether or not the minimum latency scheduling problem is NP-hard, when the nodes are placed in the Euclidean plane and arbitrary power levels can be chosen for the transmissions. We resolve this open question for all path loss exponent values $\alpha \geq 3$.

Connected through hyperedge HE-1 (induced by source paper "effective wireless scheduling via hypergraph sketches"):
  with members:
    - "wireless link capacity under shadowing and fading"
    - "the price of local power control in wireless scheduling"
    - "how well can graphs represent wireless interference"
    - "beyond geometry towards fully realistic wireless models"
    - "jamming resistant learning in wireless networks"
    - "online independent set beyond the worst case secretaries prophets and periods"
    - "dynamic packet scheduling in wireless networks"
    - "algorithms for wireless capacity"

Connected through hyperedge HE-2 (induced by source paper "universal framework for wireless scheduling problems"):
  with members:
    - "the price of local power control in wireless scheduling"
    - "how well can graphs represent wireless interference"
    - "wireless capacity and admission control in cognitive radio"
    - "wireless capacity with oblivious power in general metrics"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "wireless scheduling with power control"
    - "fast mixing of parallel glauber dynamics and low delay csma scheduling"
    - "opportunity cost algorithms for combinatorial auctions"

Connected through hyperedge HE-3 (induced by source paper "the price of local power control in wireless scheduling"):
  with members:
    - "how well can graphs represent wireless interference"
    - "beyond geometry towards fully realistic wireless models"
    - "wireless scheduling algorithms in complex environments"
    - "on the impact of geometry on ad hoc communication in wireless networks"
    - "approximation algorithms for wireless link scheduling with flexible data rates"
    - "the power of non uniform wireless power"
    - "towards tight bounds for local broadcasting"
    - "algorithms for wireless capacity"

Connected through hyperedge HE-4 (induced by source paper "how well can graphs represent wireless interference"):
  with members:
    - "beyond geometry towards fully realistic wireless models"
    - "wireless scheduling algorithms in complex environments"
    - "approximation algorithms for wireless link scheduling with flexible data rates"
    - "dynamic packet scheduling in wireless networks"
    - "algorithms for wireless capacity"
    - "secondary spectrum auctions for symmetric and submodular bidders"
    - "wireless capacity and admission control in cognitive radio"
    - "wireless connectivity and capacity"

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)