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: "joint routing scheduling and power control providing hard deadline in wireless multihop networks"
  Abstract: We consider optimal/efficient power allocation policies in a single/multihop wireless network in the presence of hard end-to-end deadline delay constraints on the transmitted packets. Such constraints can be useful for real time voice and video. Power is consumed in only transmission of the data. We consider the case when the power used in transmission is a convex function of the data transmitted. We develop a computationally efficient online algorithm, which minimizes the average power for the single hop. We model this problem as dynamic program (DP) and obtain the optimal solution. Next, we generalize it to the multiuser, multihop scenario when there are multiple real time streams with different hard deadline constraints.

Connected through hyperedge HE-1 (induced by source paper "a distributed scheduling algorithm to provide quality of service in multihop wireless networks"):
  with members:
    - "a distributed algorithm for quality of service provisioning in multihop networks"
    - "throughput optimal decentralized scheduling of multi hop networks with end to end deadline constraints unreliable links"
    - "enhancing the delay performance of dynamic backpressure algorithms"
    - "incremental gradient subgradient and proximal methods for convex optimization a survey"
    - "a survey on delay aware resource control for wireless systems large deviation theory stochastic lyapunov drift and distributed stochastic learning"

Connected through hyperedge HE-2 (induced by source paper "distributed control and quality of service in multihop wireless networks"):
  with members:
    - "throughput optimal decentralized scheduling of multi hop networks with end to end deadline constraints unreliable links"
    - "enhancing the delay performance of dynamic backpressure algorithms"
    - "incremental gradient subgradient and proximal methods for convex optimization a survey"
    - "a survey on delay aware resource control for wireless systems large deviation theory stochastic lyapunov drift and distributed stochastic learning"

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)