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: "scalable wake up of multi channel single hop radio networks"
  Abstract: We consider single-hop radio networks with multiple channels as a model of wireless networks. There are n stations connected to b radio channels that do not provide collision detection. A station uses all the channels concurrently and independently. Some k stations may become active spontaneously at arbitrary times. The goal is to wake up the network, which occurs when all the stations hear a successful transmission on some channel. Duration of a waking-up execution is measured starting from the first spontaneous activation. We present a deterministic algorithm that wakes up a network in O ( k log 1 / b ? k log ? n ) time, where k is unknown. We give a deterministic scalable algorithm for the special case when b d log ? log ? n , for some constant d 1 , which wakes up a network in O ( k b log ? n log ? ( b log ? n ) ) time, with k unknown. This algorithm misses time optimality by at most a factor of O ( log ? n ( log ? b + log ? log ? n ) ) , because any deterministic algorithm requires ? ( k b log ? n k ) time. We give a randomized algorithm that wakes up a network within O ( k 1 / b ln ? 1 ? ) rounds with a probability that is at least 1 - ? , for any 0 < ? < 1 , where k is known. We also consider a model of jamming, in which each channel in any round may be jammed to prevent a successful transmission, which happens with some known parameter probability p, independently across all channels and rounds. For this model, we give two deterministic algorithms for unknown k: one wakes up a network in time O ( log - 1 ? ( 1 p ) k log ? n log 1 / b ? k ) , and the other in time O ( log - 1 ? ( 1 p ) k b log ? n log ? ( b log ? n ) ) when the inequality b log ? ( 128 b log ? n ) holds, both with probabilities that are at least 1 - 1 / poly ( n ) .

Connected through hyperedge HE-1 (induced by source paper "singletons for simpletons revisiting windowed backoff using chernoff bounds"):
  with members:
    - "the energy complexity of broadcast"
    - "exponential separations in the energy complexity of leader election"
    - "fast and robust compressive phase retrieval with sparse graph codes"
    - "unbounded contention resolution in multiple access channels"
    - "a jamming resistant mac protocol for multi hop wireless networks"

Connected through hyperedge HE-2 (induced by source paper "packet latency of deterministic broadcasting in adversarial multiple access channels"):
  with members:
    - "randomized communication in radio networks"
    - "broadcasting in ad hoc multiple access channels"
    - "competitive mac under adversarial sinr"
    - "adversarial multiple access channels with individual injection rates"
    - "unbounded contention resolution in multiple access channels"
    - "maximum throughput of multiple access channels in adversarial environments"
    - "source routing and scheduling in packet networks"

Connected through hyperedge HE-3 (induced by source paper "naming a channel with beeps"):
  with members:
    - "randomized communication in radio networks"
    - "asynchronous broadcasting with bivalent beeps"
    - "feedback from nature simple randomised distributed algorithms for maximal independent set selection and greedy colouring"
    - "the computational power of beeps"
    - "anonymous processors with synchronous shared memory"
    - "communicating with beeps"
    - "randomized broadcast in radio networks with collision detection"
    - "beeping a maximal independent set"

Connected through hyperedge HE-4 (induced by source paper "counting in one hop beeping networks"):
  with members:
    - "randomized communication in radio networks"
    - "design patterns in beeping algorithms"
    - "design patterns in beeping algorithms examples emulation and analysis"
    - "the computational power of beeps"
    - "naming and counting in anonymous unknown dynamic networks"
    - "beeping a maximal independent set"
    - "feedback from nature an optimal distributed algorithm for maximal independent set selection"
    - "deploying wireless networks with beeps"

Connected through hyperedge HE-5 (induced by source paper "uniform information exchange in multi channel wireless ad hoc networks"):
  with members:
    - "unbounded contention resolution in multiple access channels"

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)