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: "throughput scaling in random wireless networks a non hierarchical multipath routing strategy"
  Abstract: Franceschetti et al. have recently shown that per-node throughput in an extended, ad hoc wireless network with $\Theta(n)$ randomly distributed nodes and multihop routing can be increased from the $\Omega({1 \over \sqrt{n} \log n})$ scaling demonstrated in the seminal paper of Gupta and Kumar to $\Omega({1 \over \sqrt{n}})$. The goal of the present paper is to understand the dependence of this interesting result on the principal new features it introduced relative to Gupta-Kumar: (1) a capacity-based formula for link transmission bit-rates in terms of received signal-to-interference-and-noise ratio (SINR); (2) hierarchical routing from sources to destinations through a system of communal highways; and (3) cell-based routes constructed by percolation. The conclusion of the present paper is that the improved throughput scaling is principally due to the percolation-based routing, which enables shorter hops and, consequently, less interference. This is established by showing that throughput $\Omega({1 \over \sqrt{n}})$ can be attained by a system that does not employ highways, but instead uses percolation to establish, for each source-destination pair, a set of $\Theta(\log n)$ routes within a narrow routing corridor running from source to destination. As a result, highways are not essential. In addition, it is shown that throughput $\Omega({1 \over \sqrt{n}})$ can be attained with the original threshold transmission bit-rate model, provided that node transmission powers are permitted to grow with $n$. Thus, the benefit of the capacity bit-rate model is simply to permit the power to remain bounded, even as the network expands.

Connected through hyperedge HE-1 (induced by source paper "capacity of large scale csma wireless networks"):
  with members:
    - "effective carrier sensing in csma networks under cumulative interference"
    - "safe carrier sensing range in csma network under physical interference model"
    - "rethinking information theory for mobile ad hoc networks"
    - "throughput and delay analysis of wireless random access networks"
    - "back of the envelope computation of throughput distributions in csma wireless networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-2 (induced by source paper "throughput and delay scaling in supportive two tier networks"):
  with members:
    - "cognitive networks achieve throughput scaling of a homogeneous network"
    - "scaling laws for overlaid wireless networks a cognitive radio network vs a primary network"
    - "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.IT(Information Theory)