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: "effects of mac approaches on non monotonic saturation with cope a simple case study"
  Abstract: We construct a simple network model to provide insight into network design strategies. We show that the model can be used to address various approaches to network coding, MAC, and multi-packet reception so that their effects on network throughput can be evaluated. We consider several topology components which exhibit the same non-monotonic saturation behavior found within the Katti et. al. COPE experiments. We further show that fairness allocation by the MAC can seriously impact performance and cause this non-monotonic saturation. Using our model, we develop a MAC that provides monotonic saturation, higher saturation throughput gains and fairness among flows rather than nodes. The proposed model provides an estimate of the achievable gains for the cross-layer design of network coding, multi-packet reception, and MAC showing that super-additive throughput gains on the order of six times that of routing are possible.

Connected through hyperedge HE-1 (induced by source paper "a markov chain model for the decoding probability of sparse network coding"):
  with members:
    - "analysis and optimization of sparse random linear network coding for reliable multicast services"
    - "fulcrum network codes a code for fluid allocation of complexity"
    - "batched sparse codes"
    - "network coding meets tcp"

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)