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: "sinr diagrams towards algorithmically usable sinr models of wireless networks"
  Abstract: The rules governing the availability and quality of connections in a wireless network are described by physical models such as the signal-to-interference & noise ratio (SINR) model. For a collection of simultaneously transmitting stations in the plane, it is possible to identify a reception zone for each station, consisting of the points where its transmission is received correctly. The resulting SINR diagram partitions the plane into a reception zone per station and the remaining plane where no station can be heard. #R##N#SINR diagrams appear to be fundamental to understanding the behavior of wireless networks, and may play a key role in the development of suitable algorithms for such networks, analogous perhaps to the role played by Voronoi diagrams in the study of proximity queries and related issues in computational geometry. So far, however, the properties of SINR diagrams have not been studied systematically, and most algorithmic studies in wireless networking rely on simplified graph-based models such as the unit disk graph (UDG) model, which conveniently abstract away interference-related complications, and make it easier to handle algorithmic issues, but consequently fail to capture accurately some important aspects of wireless networks. #R##N#The current paper focuses on obtaining some basic understanding of SINR diagrams, their properties and their usability in algorithmic applications. Specifically, based on some algebraic properties of the polynomials defining the reception zones we show that assuming uniform power transmissions, the reception zones are convex and relatively well-rounded. These results are then used to develop an efficient approximation algorithm for a fundamental point location problem in wireless networks.

Connected through hyperedge HE-1 (induced by source paper "is our model for contention resolution wrong"):
  with members:
    - "competitive mac under adversarial sinr"
    - "adversarial multiple access channels with individual injection rates"

Connected through hyperedge HE-2 (induced by source paper "braess s paradox in wireless networks the danger of improved technology"):
  with members:
    - "sinr diagram with interference cancellation"
    - "the topology of wireless communication"
    - "wireless connectivity and capacity"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "on a game theoretic approach to capacity maximization in wireless networks"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-3 (induced by source paper "sinr diagram with interference cancellation"):
  with members:
    - "open loop spatial multiplexing and diversity communications in ad hoc networks"
    - "the topology of wireless communication"
    - "gaussian interference channel capacity to within one bit"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-4 (induced by source paper "algorithms for wireless capacity"):
  with members:
    - "approximation algorithms for wireless link scheduling with flexible data rates"
    - "the power of non uniform wireless power"
    - "a fully distributed algorithm for throughput performance in wireless networks"
    - "wireless capacity and admission control in cognitive radio"
    - "wireless connectivity and capacity"
    - "wireless capacity with oblivious power in general metrics"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"
    - "on a game theoretic approach to capacity maximization in wireless networks"

Connected through hyperedge HE-5 (induced by source paper "distributed deterministic broadcasting in wireless networks of weak devices under the sinr model"):
  with members:
    - "a note on uniform power connectivity in the sinr model"

Connected through hyperedge HE-6 (induced by source paper "algorithms for scheduling with power control in wireless networks"):
  with members:
    - "the topology of wireless communication"
    - "algorithms for scheduling with power control in wireless networks"
    - "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"
    - "a note on uniform power connectivity in the sinr model"

Connected through hyperedge HE-7 (induced by source paper "the topology of wireless communication"):
  with members:
    - "batched point location in sinr diagrams via algebraic tools"
    - "wireless capacity with oblivious power in general metrics"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"

Connected through hyperedge HE-8 (induced by source paper "distributed planarization and local routing strategies in sensor networks"):
  with members:
    - "on a family of strong geometric spanners that admit local routing strategies"

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)