human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "distributed control and quality of service in multihop wireless networks"):
  Abstract: Control of wireless multihop networks, while simultaneously meeting end-to-end mean delay requirements of different flows is a challenging problem. Additionally, distributed computation of control parameters adds to the complexity. Using the notion of discrete review used in fluid control of networks, a distributed algorithm is proposed for control of multihop wireless networks with interference constraints. The algorithm meets end-to-end mean delay requirements by solving an optimization problem at review instants. The optimization incorporates delay requirements as weights in the function being maximized. The weights are dynamic and vary depending on queue length information. The optimization is done in a distributed manner using an incremental gradient ascent algorithm. The stability of the network under the proposed policy is analytically studied and the policy is shown to be throughput optimal.

Includes members:
  Member "joint routing scheduling and power control providing hard deadline in wireless multihop networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a distributed scheduling algorithm to provide quality of service in multihop wireless networks")
  Member "throughput optimal decentralized scheduling of multi hop networks with end to end deadline constraints unreliable links":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "quality of service in multihop wireless networks diffusion approximation")
  Member "enhancing the delay performance of dynamic backpressure algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adaptive matching for expert systems with uncertain task types")
  Member "incremental gradient subgradient and proximal methods for convex optimization a survey":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the impact of neural network overparameterization on gradient confusion and stochastic gradient descent")
  Member "a survey on delay aware resource control for wireless systems large deviation theory stochastic lyapunov drift and distributed stochastic learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint optimization of file placement and delivery in cache assisted wireless networks with limited lifetime and cache space")

Question: Please tell me which class the source paper 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)