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 "counting in one hop beeping networks"):
  Abstract: We consider networks of processes which interact with beeps. In the basic model defined by Cornejo and Kuhn, which we refer to as the $BL$ variant, processes can choose in each round either to beep or to listen. Those who beep are unable to detect simultaneous beeps. Those who listen can only distinguish between silence and the presence of at least one beep. Beeping models are weak in essence and even simple tasks may become difficult or unfeasible with them. #R##N#In this paper, we address the problem of computing how many participants there are in a one-hop network: the {\em counting} problem. We first observe that no algorithm can compute this number with certainty in $BL$, whether the algorithm be deterministic or even randomised (Las Vegas). We thus consider the stronger variant where beeping nodes are able to detect simultaneous beeps, referred to as $B_{cd}L$ (for {\em collision detection}). We prove that at least $n$ rounds are necessary in $B_{cd}L$, and we present an algorithm whose running time is $O(n)$ rounds with high probability. Further experimental results show that its expected running time is less than $10n$. Finally, we discuss how this algorithm can be adapted in other beeping models. In particular, we show that it can be emulated in $BL$, at the cost of a logarithmic slowdown and of trading its Las Vegas nature (result certain, time uncertain) against Monte Carlo (time certain, result uncertain).

Includes members:
  Member "randomized communication in radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "packet oblivious stable routing in multi hop wireless networks")
  Member "design patterns in beeping algorithms":
    also connected through other hyperedges:
      (none)
  Member "scalable wake up of multi channel single hop radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "singletons for simpletons revisiting windowed backoff using chernoff bounds")
  Member "design patterns in beeping algorithms examples emulation and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed voting in beep model")
  Member "the computational power of beeps":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed voting in beep model")
  Member "naming and counting in anonymous unknown dynamic networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed computation and reconfiguration in actively dynamic networks")
  Member "beeping a maximal independent set":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed voting in beep model")
  Member "feedback from nature an optimal distributed algorithm for maximal independent set selection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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.DC(Distributed, Parallel, and Cluster Computing)