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 "multi path alpha fair resource allocation at scale in distributed software defined networks"):
  Abstract: The performance of computer networks relies on how bandwidth is shared among different flows. Fair resource allocation is a challenging problem particularly when the flows evolve over time. To address this issue, bandwidth sharing techniques that quickly react to the traffic fluctuations are of interest, especially in large-scale settings with hundreds of nodes and thousands of flows. In this context, we propose a distributed algorithm based on the alternating direction method of multipliers (ADMM) that tackles the multi-path fair resource allocation problem in a distributed SDN control architecture. Our ADMM-based algorithm continuously generates a sequence of resource allocation solutions converging to the fair allocation while always remaining feasible, a property that standard primal–dual decomposition methods often lack. Thanks to the distribution of all computer intensive operations, we demonstrate that we can handle large instances at scale.

Includes members:
  Member "lower bounds for the fair resource allocation problem":
    also connected through other hyperedges:
      (none)
  Member "real time fair resource allocation in distributed software defined networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lower bounds for the fair resource allocation problem")
  Member "asynchronous distributed admm for large scale optimization part i algorithm and convergence analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "async a cloud engine with asynchrony and history for distributed machine learning")
  Member "a fast distributed stateless algorithm for alpha fair packing problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "width independence beyond linear objectives distributed fair packing and covering algorithms")
  Member "software defined networking a comprehensive survey":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "disco distributed multi domain sdn controllers":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "survey of consistent software defined network updates")
  Member "optimization with sparsity inducing penalties":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sparse optimization for green edge ai inference")
  Member "congestion control with explicit rate indication":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "max min fair rate allocation and routing in energy harvesting networks algorithmic analysis")

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)