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 "deterministic backbone creation in an sinr network without knowledge of location"):
  Abstract: For a given network, a backbone is an overlay network consisting of a connected dominating set with additional accessibility properties. Once a backbone is created for a network, it can be utilized for fast communication amongst the nodes of the network. #R##N#The Signal-to-Interference-plus-Noise-Ratio (SINR) model has become the standard for modeling communication among devices in wireless networks. For this model, the community has pondered what the most realistic solutions for communication problems in wireless networks would look like. Such solutions would have the characteristic that they would make the least number of assumptions about the availability of information about the participating nodes. Solving problems when nothing at all is known about the network and having nodes just start participating would be ideal. However, this is quite challenging and most likely not feasible. The pragmatic approach is then to make meaningful assumptions about the available information and present efficient solutions based on this information. #R##N#We present a solution for creation of backbone in the SINR model, when nodes do not have access to their physical coordinates or the coordinates of other nodes in the network. This restriction models the deployment of nodes in various situations for sensing hurricanes, cyclones, and so on, where only information about nodes prior to their deployment may be known but not their actual locations post deployment. We assume that nodes have access to knowledge of their label, the labels of nodes within their neighborhood, the range from which labels are taken $[N]$ and the total number of participating nodes $n$. We also assume that nodes wake up spontaneously. We present an efficient deterministic protocol to create a backbone with a round complexity of $O(\Delta \lg^2 N)$.

Includes members:
  Member "achieving dilution without knowledge of coordinates in the sinr model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deterministic protocols in the sinr model without knowledge of coordinates")
  Member "deterministic protocols in the sinr model without knowledge of coordinates":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "achieving dilution without knowledge of coordinates in the sinr model")
  Member "distributed bare bones communication in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "data dissemination in unified dynamic wireless networks")
  Member "multi broadcasting under the sinr model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deterministic protocols in the sinr model without knowledge of coordinates")
  Member "distributed communication in bare bones wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deterministic protocols in the sinr model without knowledge of coordinates")
  Member "almost optimal cover free families":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exact learning from an honest teacher that answers membership queries")
  Member "distributed deterministic broadcasting in wireless networks under the sinr model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "achieving dilution without knowledge of coordinates in the sinr model")

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.DC(Distributed, Parallel, and Cluster Computing)