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: "randomized broadcast in radio networks with collision detection"
  Abstract: We present a randomized distributed algorithm that in radio networks with collision detection broadcasts a single message in $O(D + \log^6 n)$ rounds, with high probability. This time complexity is most interesting because of its optimal additive dependence on the network diameter $D$. It improves over the currently best known $O(D\log\frac{n}{D}\,+\,\log^2 n)$ algorithms, due to Czumaj and Rytter [FOCS 2003], and Kowalski and Pelc [PODC 2003]. These algorithms where designed for the model without collision detection and are optimal in that model. However, as explicitly stated by Peleg in his 2007 survey on broadcast in radio networks, it had remained an open question whether the bound can be improved with collision detection. #R##N#We also study distributed algorithms for broadcasting $k$ messages from a single source to all nodes. This problem is a natural and important generalization of the single-message broadcast problem, but is in fact considerably more challenging and less understood. We show the following results: If the network topology is known to all nodes, then a $k$-message broadcast can be performed in $O(D + k\log n + \log^2 n)$ rounds, with high probability. If the topology is not known, but collision detection is available, then a $k$-message broadcast can be performed in $O(D + k\log n + \log^6 n)$ rounds, with high probability. The first bound is optimal and the second is optimal modulo the additive $O(\log^6 n)$ term.

Connected through hyperedge HE-1 (induced by source paper "competitive broadcast against adaptive adversary in multi channel radio networks"):
  with members:
    - "fast and resource competitive broadcast in multi channel radio networks"
    - "the energy complexity of broadcast"
    - "exploiting spontaneous transmissions for broadcasting and leader election in radio networks"
    - "exponential separations in the energy complexity of leader election"
    - "interactive communication with unknown noise rate"
    - "making evildoers pay resource competitive broadcast in sensor networks"
    - "a resource competitive jamming defense"

Connected through hyperedge HE-2 (induced by source paper "fast and resource competitive broadcast in multi channel radio networks"):
  with members:
    - "the energy complexity of broadcast"
    - "exploiting spontaneous transmissions for broadcasting and leader election in radio networks"
    - "making evildoers pay resource competitive broadcast in sensor networks"
    - "a resource competitive jamming defense"

Connected through hyperedge HE-3 (induced by source paper "randomized communication without network knowledge"):
  with members:
    - "deterministic blind radio networks"
    - "deterministic communication in radio networks"
    - "exploiting spontaneous transmissions for broadcasting and leader election in radio networks"
    - "communicating with beeps"

Connected through hyperedge HE-4 (induced by source paper "erasure correction for noisy radio networks"):
  with members:
    - "broadcasting in noisy radio networks"
    - "multi message broadcast with abstract mac layers and unreliable links"
    - "interactive channel capacity revisited"
    - "bounds on contention management in radio networks"

Connected through hyperedge HE-5 (induced by source paper "deterministic communication in radio networks"):
  with members:
    - "near optimal leader election in multi hop radio networks"
    - "information dissemination in unknown radio networks with large labels"

Connected through hyperedge HE-6 (induced by source paper "broadcasting in noisy radio networks"):
  with members:
    - "broadcast throughput in radio networks routing vs network coding"
    - "a new perspective on vertex connectivity"
    - "fast structuring of radio networks large for multi message communications"
    - "bounds on contention management in radio networks"
    - "analyzing network coding gossip made easy"
    - "on distributed computation in noisy random planar networks"

Connected through hyperedge HE-7 (induced by source paper "the energy complexity of broadcast"):
  with members:
    - "exploiting spontaneous transmissions for broadcasting and leader election in radio networks"
    - "exponential separations in the energy complexity of leader election"
    - "radio network lower bounds made easy"
    - "parallel graph decompositions using random shifts"
    - "near optimal leader election in multi hop radio networks"

Connected through hyperedge HE-8 (induced by source paper "latency optimal broadcasting in noisy wireless mesh networks"):
  with members:
    - "broadcasting in noisy radio networks"
    - "broadcast throughput in radio networks routing vs network coding"
    - "fast structuring of radio networks large for multi message communications"
    - "analyzing network coding gossip made easy"

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.DS(Data Structures and Algorithms)