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: "swim a simple model to generate small mobile worlds"
  Abstract: This paper presents small world in motion (SWIM), a new mobility model for ad-hoc networking. SWIM is relatively simple, is easily tuned by setting just a few parameters, and generates traces that look real--synthetic traces have the same statistical properties of real traces. SWIM shows experimentally and theoretically the presence of the power law and exponential decay dichotomy of inter-contact time, and, most importantly, our experiments show that it can predict very accurately the performance of forwarding protocols.

Connected through hyperedge HE-1 (induced by source paper "lightweight joint simulation of vehicular mobility and communication with limosim"):
  with members:
    - "car to cloud communication traffic analysis based on the common vehicle information model"
    - "limosim a lightweight and integrated approach for simulating vehicular mobility with omnet"
    - "b a t mobile leveraging mobility control knowledge for efficient routing in mobile robotic networks"
    - "a survey of anticipatory mobile networking context based classification prediction methodologies and optimization techniques"

Connected through hyperedge HE-2 (induced by source paper "opportunistic networking protocol simulator for omnet"):
  with members:
    - "simulating opportunistic networks survey and future directions"

Connected through hyperedge HE-3 (induced by source paper "groups net group meetings aware routing in multi hop d2d networks"):
  with members:
    - "group mobility detection tracking and characterization"
    - "a survey on device to device communication in cellular networks"
    - "an overview on 3gpp device to device proximity services"
    - "on the dynamics of human proximity for data diffusion in ad hoc networks"
    - "estimating network parameters for selecting community detection algorithms"

Connected through hyperedge HE-4 (induced by source paper "coverage analysis of information dissemination in throwbox augmented dtn"):
  with members:
    - "information filtering via balanced diffusion on bipartite networks"
    - "information filtering in sparse online systems recommendation via semi local diffusion"

Connected through hyperedge HE-5 (induced by source paper "socially aware networking a survey"):
  with members:
    - "beyond traditional dtn routing social networks for opportunistic communication"
    - "dtn routing in a mobility pattern space"

Connected through hyperedge HE-6 (induced by source paper "a survey on routing and data dissemination in opportunistic mobile social networks"):
  with members:
    - "opportunistic routing based on daily routines"
    - "intrinsically dynamic network communities"
    - "coalitional game theory for communication networks a tutorial"

Connected through hyperedge HE-7 (induced by source paper "flooding time in opportunistic networks under power law and exponential inter contact times"):
  with members:
    - "tight bounds on information dissemination in sparse mobile networks"
    - "information spreading in stationary markovian evolving graphs"
    - "information propagation speed in mobile and delay tolerant networks"
    - "manets high mobility can make up for low transmission power"

Connected through hyperedge HE-8 (induced by source paper "fast flooding over manhattan"):
  with members:
    - "information spreading in dynamic graphs"
    - "tight bounds on information dissemination in sparse mobile networks"
    - "information spreading in stationary markovian evolving graphs"
    - "modelling mobility a discrete revolution"
    - "information propagation speed in mobile and delay tolerant networks"
    - "manets high mobility can make up for low transmission power"

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)