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: "time vs information tradeoffs for leader election in anonymous trees"
  Abstract: The leader election task calls for all nodes of a network to agree on a single node. If the nodes of the network are anonymous, the task of leader election is formulated as follows: every node $v$ of the network must output a simple path, coded as a sequence of port numbers, such that all these paths end at a common node, the leader. In this paper, we study deterministic leader election in anonymous trees. #R##N#Our aim is to establish tradeoffs between the allocated time $\tau$ and the amount of information that has to be given $\textit{a priori}$ to the nodes to enable leader election in time $\tau$ in all trees for which leader election in this time is at all possible. Following the framework of $\textit{algorithms with advice}$, this information (a single binary string) is provided to all nodes at the start by an oracle knowing the entire tree. The length of this string is called the $\textit{size of advice}$. For an allocated time $\tau$, we give upper and lower bounds on the minimum size of advice sufficient to perform leader election in time $\tau$. #R##N#We consider $n$-node trees of diameter $diam \leq D$. While leader election in time $diam$ can be performed without any advice, for time $diam-1$ we give tight upper and lower bounds of $\Theta (\log D)$. For time $diam-2$ we give tight upper and lower bounds of $\Theta (\log D)$ for even values of $diam$, and tight upper and lower bounds of $\Theta (\log n)$ for odd values of $diam$. For the time interval $[\beta \cdot diam, diam-3]$ for constant $\beta >1/2$, we prove an upper bound of $O(\frac{n\log n}{D})$ and a lower bound of $\Omega(\frac{n}{D})$, the latter being valid whenever $diam$ is odd or when the time is at most $diam-4$. Finally, for time $\alpha \cdot diam$ for any constant $\alpha <1/2$ (except for the case of very small diameters), we give tight upper and lower bounds of $\Theta (n)$.

Connected through hyperedge HE-1 (induced by source paper "deterministic leader election in anonymous radio networks"):
  with members:
    - "exploiting spontaneous transmissions for broadcasting and leader election in radio networks"
    - "deterministic leader election in o d log n time with messages of size o 1"

Connected through hyperedge HE-2 (induced by source paper "cost vs information tradeoffs for treasure hunt in the plane"):
  with members:
    - "information complexity of treasure hunt in geometric terrains"
    - "the graph exploration problem with advice"
    - "reaching a target in the plane with no information"
    - "impact of knowledge on election time in anonymous networks"
    - "topology recognition with advice"
    - "deterministic graph exploration with advice"
    - "tradeoffs between cost and information for rendezvous and treasure hunt"

Connected through hyperedge HE-3 (induced by source paper "wireless broadcast with short labelling"):
  with members:
    - "markovian model for broadcast in wireless body area networks"
    - "ban gzkp optimal zero knowledge proof based scheme for wireless body area networks"
    - "peak transmission rate resilient crosslayer broadcast for body area networks"
    - "finding the size of a radio network with short labels"
    - "total order reliable convergecast in wban"
    - "ubiquitous healthcare in wireless body area networks a survey"

Connected through hyperedge HE-4 (induced by source paper "wireless broadcast with optimal labelling"):
  with members:
    - "ban gzkp optimal zero knowledge proof based scheme for wireless body area networks"
    - "peak transmission rate resilient crosslayer broadcast for body area networks"
    - "constant length labeling schemes for deterministic radio broadcast"
    - "finding the size of a radio network with short labels"
    - "total order reliable convergecast in wban"

Connected through hyperedge HE-5 (induced by source paper "almost logarithmic time space optimal leader election in population protocols"):
  with members:
    - "fast space optimal leader election in population protocols"
    - "logarithmic expected time leader election in population protocol model"
    - "space optimal majority in population protocols"
    - "time space trade offs in population protocols"
    - "on convergence and threshold properties of discrete lotka volterra population protocols"
    - "stable leader election in population protocols requires linear time"
    - "plurality consensus in the gossip model"
    - "leader election for anonymous asynchronous agents in arbitrary networks"

Connected through hyperedge HE-6 (induced by source paper "information complexity of treasure hunt in geometric terrains"):
  with members:
    - "the graph exploration problem with advice"
    - "reaching a target in the plane with no information"
    - "impact of knowledge on election time in anonymous networks"
    - "topology recognition with advice"
    - "deterministic graph exploration with advice"

Connected through hyperedge HE-7 (induced by source paper "finding the size of a radio network with short labels"):
  with members:
    - "short labeling schemes for topology recognition in wireless tree networks"
    - "exploiting spontaneous transmissions for broadcasting and leader election in radio networks"
    - "topology recognition with advice"
    - "randomized broadcast in radio networks with collision detection"

Connected through hyperedge HE-8 (induced by source paper "constant length labeling schemes for deterministic radio broadcast"):
  with members:
    - "short labeling schemes for topology recognition in wireless tree networks"
    - "finding the size of a radio network with short labels"
    - "topology recognition with advice"

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)