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: "on the delay advantage of coding in packet erasure networks"
  Abstract: We consider the delay of network coding compared to routing with retransmissions in packet erasure networks with probabilistic erasures. We investigate the sub-linear term in the block delay required for unicasting $n$ packets and show that there is an unbounded gap between network coding and routing. In particular, we show that delay benefit of network coding scales at least as $\sqrt{n}$. Our analysis of the delay function for the routing strategy involves a major technical challenge of computing the expectation of the maximum of two negative binomial random variables. This problem has been studied previously and we derive the first exact characterization which may be of independent interest. We also use a martingale bounded differences argument to show that the actual coding delay is tightly concentrated around its expectation.

Connected through hyperedge HE-1 (induced by source paper "adaptive causal network coding with feedback"):
  with members:
    - "resource allocation and harq optimization for urllc traffic in 5g wireless networks"
    - "tiny codes for guaranteeable delay"
    - "complete mdp convolutional codes"
    - "throughput maximization for delay sensitive random access communication"
    - "analysis of feedback error in automatic repeat request"
    - "low delay random linear coding over a stream"
    - "the effect of block wise feedback on the throughput delay trade off in streaming"
    - "an elias bound on the bhattacharyya distance of codes for channels with a zero error capacity"

Connected through hyperedge HE-2 (induced by source paper "delay on broadcast erasure channels under random linear combinations"):
  with members:
    - "throughput of rateless codes over broadcast erasure channels"
    - "throughput delay analysis of random linear network coding for wireless broadcasting"
    - "coding for errors and erasures in random network coding"

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.IT(Information Theory)