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: "efficient resource allocation for on demand mobile edge cloud computing"
  Abstract: Mobile-edge cloud computing is a new paradigm to provide cloud computing capabilities at the edge of pervasive radio access networks in close proximity to mobile users. Aiming at provisioning flexible on-demand mobile-edge cloud service, in this paper we propose a comprehensive framework consisting of a resource-efficient computation offloading mechanism for users and a joint communication and computation (JCC) resource allocation mechanism for network operator. Specifically, we first study the resource-efficient computation offloading problem for a user, in order to reduce user's resource occupation by determining its optimal communication and computation resource profile with minimum resource occupation and meanwhile satisfying the QoS constraint. We then tackle the critical problem of user admission control for JCC resource allocation, in order to properly select the set of users for resource demand satisfaction. We show the admission control problem is NP-hard, and hence develop an efficient approximation solution of a low complexity by carefully designing the user ranking criteria and rigourously derive its performance guarantee. To prevent the manipulation that some users may untruthfully report their valuations in acquiring mobile-edge cloud service, we further resort to the powerful tool of critical value approach to design truthful pricing scheme for JCC resource allocation. Extensive performance evaluation demonstrates that the proposed schemes can achieve superior performance for on-demand mobile-edge cloud computing.

Connected through hyperedge HE-1 (induced by source paper "edge ai on demand accelerating deep neural network inference via edge computing"):
  with members:
    - "edge intelligence paving the last mile of artificial intelligence with edge computing"
    - "zygarde time sensitive on device deep intelligence on intermittently powered systems"
    - "jointdnn an efficient training and inference engine for intelligent mobile cloud computing services"
    - "musical chair efficient real time recognition using collaborative iot devices"
    - "edge intelligence on demand deep learning model co inference with device edge synergy"
    - "efficient neural architecture search via parameter sharing"
    - "progressive neural architecture search"
    - "a survey on mobile edge computing the communication perspective"

Connected through hyperedge HE-2 (induced by source paper "follow me at the edge mobility aware dynamic service placement for mobile edge computing"):
  with members:
    - "edge intelligence on demand deep learning model co inference with device edge synergy"
    - "exploiting massive d2d collaboration for energy efficient mobile edge computing"
    - "emm energy aware mobility management for mobile edge computing in ultra dense networks"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "toward hierarchical mobile edge computing an auction based profit maximization approach"
    - "dynamic service placement for mobile micro clouds with predicted future costs"
    - "a non stochastic learning approach to energy efficient mobility management"
    - "dynamic service migration in mobile edge clouds"

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)