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: "differentiated end to end internet services using a weighted proportional fair sharing tcp"
  Abstract: In this document we study the application of weighted proportional fairness to data flows in the Internet. We let the users set the weights of their connections in order to maximise the utility they get from the network. When combined with a pricing scheme where connections are billed by weight and time, such a system is known to maximise the total utility of the network. Our study case is a national Web cache server connected to long distance links. We propose two ways of weighting TCP connections by manipulating some parameters of the protocol and present results from simulations and prototypes. We finally discuss how proportional fairness could be used to implement an Internet with differentiated services.

Connected through hyperedge HE-1 (induced by source paper "elasticity detection a building block for delay sensitive congestion control"):
  with members:
    - "pcc re architecting congestion control for consistent high performance"

Connected through hyperedge HE-2 (induced by source paper "enabling work conserving bandwidth guarantees for multi tenant datacenters via dynamic tenant eue binding"):
  with members:
    - "finishing flows quickly with preemptive scheduling"
    - "jellyfish networking data centers randomly"

Connected through hyperedge HE-3 (induced by source paper "agile sd a linux based tcp congestion control algorithm for supporting high speed and short distance networks"):
  with members:
    - "comparative study of high speed linux tcp variants over high bdp networks"
    - "performance evaluation of parallel tcp and its impact on bandwidth utilization and fairness in high bdp networks based on test bed"
    - "test bed based comparison of single and parallel tcp and the impact of parallelism on throughput and fairness in heterogenous networks"
    - "market oriented cloud computing vision hype and reality for delivering it services as computing utilities"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-4 (induced by source paper "performance evaluation of parallel tcp and its impact on bandwidth utilization and fairness in high bdp networks based on test bed"):
  with members:
    - "test bed based comparison of single and parallel tcp and the impact of parallelism on throughput and fairness in heterogenous networks"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-5 (induced by source paper "flow splitting with fate sharing in a next generation transport services architecture"):
  with members:
    - "peer to peer communication across network address translators"

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)