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: "storage and search in dynamic peer to peer networks"
  Abstract: We study robust and efficient distributed algorithms for searching, storing, and maintaining data in dynamic Peer-to-Peer (P2P) networks. P2P networks are highly dynamic networks that experience heavy node churn (i.e., nodes join and leave the network continuously over time). Our goal is to guarantee, despite high node churn rate, that a large number of nodes in the network can store, retrieve, and maintain a large number of data items. Our main contributions are fast randomized distributed algorithms that guarantee the above with high probability (whp) even under high adversarial churn: #R##N#1. A randomized distributed search algorithm that (whp) guarantees that searches from as many as $n - o(n)$ nodes ($n$ is the stable network size) succeed in ${O}(\log n)$-rounds despite ${O}(n/\log^{1+\delta} n)$ churn, for any small constant $\delta > 0$, per round. We assume 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, but is oblivious to the random choices made by the algorithm). #R##N#2. A storage and maintenance algorithm that guarantees (whp) data items can be efficiently stored (with only $\Theta(\log{n})$ copies of each data item) and maintained in a dynamic P2P network with churn rate up to ${O}(n/\log^{1+\delta} n)$ per round. Our search algorithm together with our storage and maintenance algorithm guarantees that as many as $n - o(n)$ nodes can efficiently store, maintain, and search even under ${O}(n/\log^{1+\delta} n)$ churn per round. Our algorithms require only polylogarithmic in $n$ bits to be processed and sent (per round) by each node. #R##N#To the best of our knowledge, our algorithms are the first-known, fully-distributed storage and search algorithms that provably work under highly dynamic settings (i.e., high churn rates per step).

Connected through hyperedge HE-1 (induced by source paper "resource competitive sybil defenses"):
  with members:
    - "proof of work without all the work"
    - "secure one way interactive communication"
    - "torbricks blocking resistant tor bridge distribution"
    - "interactive communication with unknown noise rate"
    - "bitcoin ng a scalable blockchain protocol"
    - "the mason test a defense against sybil attacks in wireless networks without trusted authorities"
    - "self healing computation"
    - "the sybil attacks and defenses a survey"

Connected through hyperedge HE-2 (induced by source paper "always be two steps ahead of your enemy"):
  with members:
    - "a self stabilizing general de bruijn graph"

Connected through hyperedge HE-3 (induced by source paper "proof of work without all the work computationally efficient attack resistant systems"):
  with members:
    - "proof of work without all the work"
    - "secure one way interactive communication"
    - "torbricks blocking resistant tor bridge distribution"
    - "interactive communication with unknown noise rate"
    - "the mason test a defense against sybil attacks in wireless networks without trusted authorities"
    - "self healing computation"
    - "the sybil attacks and defenses a survey"
    - "making evildoers pay resource competitive broadcast in sensor networks"

Connected through hyperedge HE-4 (induced by source paper "tiny groups tackle byzantine adversaries"):
  with members:
    - "proof of work without all the work"
    - "algorand the efficient and democratic ledger"
    - "self healing computation"
    - "sybilcontrol practical sybil defense with computational puzzles"
    - "breaking the o n 2 bit barrier scalable byzantine agreement with an adaptive adversary"

Connected through hyperedge HE-5 (induced by source paper "information spreading in dynamic networks under oblivious adversaries"):
  with members:
    - "lower bounds on information dissemination in dynamic networks"
    - "fast distributed computation in dynamic networks via random walks"
    - "faster information dissemination in dynamic networks via network coding"
    - "time varying graphs and dynamic networks"
    - "analyzing network coding gossip made easy"
    - "the impact of mobility on gossip algorithms"

Connected through hyperedge HE-6 (induced by source paper "distributed computation of mixing time"):
  with members:
    - "fast distributed pagerank computation"
    - "distributed random walks"
    - "nearly linear time algorithms for graph partitioning graph sparsification and solving linear systems"

Connected through hyperedge HE-7 (induced by source paper "infinite unlimited churn"):
  with members:
    - "the forgiving graph a distributed data structure for low stretch under adversarial attack"

Connected through hyperedge HE-8 (induced by source paper "discovery through gossip"):
  with members:
    - "fast distributed computation in dynamic networks via random walks"
    - "information spreading in dynamic graphs"
    - "quasirandom rumor spreading"
    - "optimal gossip based aggregate computation"

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.DC(Distributed, Parallel, and Cluster Computing)