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: "asymptotic capacity bounds for wireless networks with non uniform traffic patterns"
  Abstract: We develop bounds on the capacity of wireless multihop networks when the traffic pattern is non-uniform, i.e., not all nodes are the sources and sinks of similar volumes of traffic. Our results are asymptotic, i.e., they hold with probability going to unity as the number of nodes goes to infinity. We study (i) asymmetric networks, where the numbers of sources and destinations of traffic are unequal, (ii) multicast networks, in which each created packet has multiple destinations, (Hi) cluster networks, that consist of clients and a limited number of cluster heads, and each client wants to communicate with any one of the cluster heads, and (iv) hybrid networks, in which the nodes are supported by a limited infrastructure. Our findings quantify the fundamental capabilities of these wireless multihop networks to handle traffic bottlenecks, and point to correct design principles that achieve the capacity without resorting to overly complicated protocols.

Connected through hyperedge HE-1 (induced by source paper "asymptotic laws for joint content replication and delivery in wireless networks"):
  with members:
    - "the balanced unicast and multicast capacity regions of large wireless networks"
    - "on capacity scaling in arbitrary wireless networks"
    - "caching in wireless networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc 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.NI(Networking and Internet Architecture)