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 "noisy beeping networks"):
  Abstract: We introduce noisy beeping networks, where nodes have limited communication capabilities, namely, they can only emit energy or sense the channel for energy. Furthermore, imperfections may cause devices to malfunction with some fixed probability when sensing the channel, which amounts to deducing a noisy received transmission. Such noisy networks have implications for ultra-lightweight sensor networks and biological systems. #R##N#We show how to compute tasks in a noise-resilient manner over noisy beeping networks of arbitrary structure. In particular, we transform any algorithm that assumes a noiseless beeping network (of size $n$) into a noise-resilient version while incurring a multiplicative overhead of only $O(\log n)$ in its round complexity, with high probability. We show that our coding is optimal for some tasks, such as node-coloring of a clique. #R##N#We further show how to simulate a large family of algorithms designed for distributed networks in the CONGEST($B$) model over a noisy beeping network. The simulation succeeds with high probability and incurs an asymptotic multiplicative overhead of $O(B\cdot \Delta \cdot \min(n,\Delta^2))$ in the round complexity, where $\Delta$ is the maximal degree of the network. The overhead is tight for certain graphs, e.g., a clique. Further, this simulation implies a constant overhead coding for constant-degree networks.

Includes members:
  Member "leader election in multi hop radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "communicating with beeps")
  Member "efficient multiparty interactive coding for insertions deletions and substitutions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "small memory robust simulation of client server interactive protocols over oblivious noisy channels")
  Member "erasure correction for noisy radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "noidy conmunixatipn on the convergence of the averaging population protocol")
  Member "broadcasting in noisy radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "noidy conmunixatipn on the convergence of the averaging population protocol")
  Member "naming a channel with beeps":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed voting in beep model")
  Member "feedback from nature simple randomised distributed algorithms for maximal independent set selection and greedy colouring":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed voting in beep model")
  Member "design patterns in beeping algorithms examples emulation and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distributed voting in beep model")
  Member "communicating with beeps":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "distributed voting in beep model")

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.DS(Data Structures and Algorithms)