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: "primary user aware network coding for multi hop cognitive radio networks"
  Abstract: Network coding has proved its efficiency in increasing the network performance for traditional ad-hoc networks. In this paper, we investigate using network coding for enhancing the throughput of multi-hop cognitive radio networks. We formulate the network coding throughput maximization problem as a graph theory problem, where different constraints and primary users' characteristics are mapped to the graph structure. We then show that the optimal solution to this problem in NP-hard and propose a heuristic algorithm to efficiently solve it. #R##N#Evaluation of the proposed algorithm through NS2 simulations shows that we can increase the throughput of the constrained secondary users' network by 150\% to 200\% for a wide range of scenarios covering different primary users' densities, traffic loads, and spectrum availability.

Connected through hyperedge HE-1 (induced by source paper "cooperation based routing in cognitive radio networks"):
  with members:
    - "dead zone penetration protocol for cognitive radio networks"

Connected through hyperedge HE-2 (induced by source paper "censoring for improved sensing performance in infrastructure less cognitive radio networks"):
  with members:
    - "dead zone penetration protocol for cognitive radio 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)