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: "broadcast throughput in radio networks routing vs network coding"
  Abstract: The broadcast throughput in a network is defined as the average number of messages that can be transmitted per unit time from a given source to all other nodes when time goes to infinity.#R##N##R##N#Classical broadcast algorithms treat messages as atomic tokens and route them from the source to the receivers by making intermediate nodes store and forward messages. The more recent network coding approach, in contrast, prompts intermediate nodes to mix and code together messages. It has been shown that certain wired networks have an asymptotic network coding gap, that is, they have asymptotically higher broadcast throughput when using network coding compared to routing. Whether such a gap exists for wireless networks has been an open question of great interest. We approach this question by studying the broadcast throughput of the radio network model which has been a standard mathematical model to study wireless communication.#R##N##R##N#We show that there is a family of radio networks with a tight Θ(log log n) network coding gap, that is, networks in which the asymptotic throughput achievable via routing messages is a Θ(log log n) factor smaller than that of the optimal network coding algorithm. We also provide new tight upper and lower bounds showing that the asymptotic worst-case broadcast throughput over all networks with n nodes is Θ(1/log n) messages-per-round for both routing and network coding.

Connected through hyperedge HE-1 (induced by source paper "synchronous transmissions in low power wireless a survey of communication protocols and network services"):
  with members:
    - "feedback control goes wireless guaranteed stability over low power multi hop networks"
    - "reverse flooding exploiting radio interference for efficient propagation delay compensation in wsn clock synchronization"
    - "on the reception of concurrent transmissions in wireless sensor networks"
    - "analyzing network coding gossip made easy"

Connected through hyperedge HE-2 (induced by source paper "broadcasting in noisy radio networks"):
  with members:
    - "randomized broadcast in radio networks with collision detection"
    - "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-3 (induced by source paper "latency optimal broadcasting in noisy wireless mesh networks"):
  with members:
    - "broadcasting in noisy radio networks"
    - "randomized broadcast in radio networks with collision detection"
    - "fast structuring of radio networks large for multi message communications"
    - "analyzing network coding gossip made easy"

Connected through hyperedge HE-4 (induced by source paper "randomized broadcast in radio networks with collision detection"):
  with members:
    - "fast structuring of radio networks large for multi message communications"
    - "near optimal leader election in multi hop radio networks"
    - "analyzing network coding gossip made easy"

Connected through hyperedge HE-5 (induced by source paper "a new perspective on vertex connectivity"):
  with members:
    - "analyzing network coding gossip made easy"
    - "minimum cuts in near linear time"

Connected through hyperedge HE-6 (induced by source paper "near optimal leader election in multi hop radio networks"):
  with members:
    - "randomized broadcast in radio networks with collision detection"
    - "distributed deterministic broadcasting in uniform power ad hoc wireless networks"
    - "fast structuring of radio networks large for multi message communications"
    - "bounded contention coding for wireless networks in the high snr regime"
    - "beeping a maximal independent set"
    - "wireless connectivity and capacity"
    - "analyzing network coding gossip made easy"
    - "a constant factor approximation for wireless capacity maximization with power control in the sinr model"

Connected through hyperedge HE-7 (induced by source paper "analyzing network coding gossip made easy"):
  with members:
    - "optimal gossip with direct addressing"
    - "tight bounds for rumor spreading with vertex expansion"
    - "fast structuring of radio networks large for multi message communications"
    - "lower bounds on information dissemination in dynamic networks"
    - "bounded contention coding for wireless networks in the high snr regime"
    - "tighter worst case bounds on algebraic gossip"
    - "simple fast and deterministic gossip and rumor spreading"
    - "network coded gossip with correlated data"

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)