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 agreement in dynamic peer to peer networks"):
  Abstract: Motivated by the need for robust and fast distributed computation in highly dynamic Peer-to-Peer (P2P) networks, we study algorithms for the fundamental distributed agreement problem. P2P networks are highly dynamic networks that experience heavy node {\em churn}. Our goal is to design fast algorithms (running in a small number of rounds) that guarantee, despite high node churn rate, that almost all nodes reach a stable agreement. Our main contributions are randomized distributed algorithms that guarantee {\em stable almost-everywhere agreement} with high probability even under high adversarial churn in a polylogarithmic number of rounds: #R##N#1. An $O(\log^2 n)$-round ($n$ is the stable network size) randomized algorithm that achieves almost-everywhere agreement with high probability under up to {\em linear} churn {\em per round} (i.e., $\epsilon n$, for some small constant $\epsilon > 0$), assuming that the churn is controlled by an oblivious adversary (that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm). Our algorithm requires only polylogarithmic in $n$ bits to be processed and sent (per round) by each node. #R##N#2. An $O(\log m\log^3 n)$-round randomized algorithm that achieves almost-everywhere agreement with high probability under up to $\epsilon \sqrt{n}$ churn per round (for some small $\epsilon > 0$), where $m$ is the size of the input value domain, that works even under an adaptive adversary (that also knows the past random choices made by the algorithm). This algorithm requires up to polynomial in $n$ bits (and up to $O(\log m)$ bits) to be processed and sent (per round) by each node.

Includes members:
  Member "fast distributed computation in dynamic networks via random walks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "information spreading in dynamic networks under oblivious adversaries")
  Member "dex self healing expanders":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "some problems in compact message passing")
  Member "xheal localized self healing using expanders":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "error correction coding meets cyber physical systems message passing analysis of self healing interdependent networks")
  Member "information spreading in dynamic graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "relative hausdorff distance for network analysis")
  Member "faster information dissemination in dynamic networks via network coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "local distributed algorithms in highly dynamic networks")
  Member "time varying graphs and dynamic networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "edge disjoint branchings in temporal graphs")
  Member "breaking the o n 2 bit barrier scalable byzantine agreement with an adaptive adversary":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "in search for a linear byzantine agreement")
  Member "the effect of faults on network expansion":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "storage and search in dynamic peer to peer networks")

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)