human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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 ) .

Includes members:
  Member "packet latency of deterministic broadcasting in adversarial multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "packet oblivious stable routing in multi hop wireless networks")
  Member "uniform information exchange in multi channel wireless ad hoc networks":
    also connected through other hyperedges:
      (none)
  Member "broadcasting in ad hoc multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficient adversarial routing in shared channels")
  Member "adversarial multiple access channels with individual injection rates":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy efficient adversarial routing in shared channels")
  Member "unbounded contention resolution in multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "singletons for simpletons revisiting windowed backoff using chernoff bounds")
  Member "dynamic sharing of a multiple access channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "broadcasting in ad hoc multiple access channels")
  Member "maximum throughput of multiple access channels in adversarial environments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "energy efficient adversarial routing in shared channels")

Question: Please tell me which class the source paper 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)