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: "mobile edge computing enabled heterogeneous networks"
  Abstract: The mobile edge computing (MEC) has been introduced for providing computing capabilities at the edge of networks to improve the latency performance of wireless networks. In this paper, we provide the novel framework for MEC-enabled heterogeneous networks (HetNets) , composed of the multi-tier networks with access points (APs) (i.e., MEC servers), which have different transmission power and different computing capabilities. In this framework, we also consider multiple-type mobile users with different sizes of computation tasks, and they offload the tasks to a MEC server, and receive the computation resulting data from the server. We derive the successful edge computing probability considering both the computation and communication performance using the queueing theory and stochastic geometry. We then analyze the effects of network parameters and bias factors in MEC server association on the successful edge computing probability. We provide how the optimal bias factors in terms of successful edge computing probability can be changed according to the user type and MEC tier, and how they are different to the conventional ones that did not consider the computing capabilities and task sizes. It is also shown how the optimal bias factors can be changed when minimizing the mean latency instead of successful edge computing probability. This study provides the design insights for the optimal configuration of MEC-enabled HetNets.

Connected through hyperedge HE-1 (induced by source paper "edge computing enabled cell free massive mimo systems"):
  with members:
    - "fog massive mimo a user centric seamless hot spot architecture"
    - "joint energy minimization and resource allocation in c ran with mobile cloud"
    - "a survey on mobile edge computing the communication perspective"
    - "channel hardening and favorable propagation in cell free massive mimo with stochastic geometry"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "collaborative mobile edge computing in 5g networks new paradigms scenarios and challenges"
    - "power delay tradeoff in multi user mobile edge computing systems"
    - "cell free massive mimo uniformly great service for everyone"

Connected through hyperedge HE-2 (induced by source paper "dynamic spectrum sharing for load balancing in multi cell mobile edge computing"):
  with members:
    - "joint service placement and request routing in multi cell mobile edge computing networks"
    - "multiuser computation offloading and downloading for edge computing with virtualization"
    - "optimizing user association and spectrum allocation in hetnets a utility perspective"
    - "joint optimization of radio and computational resources for multicell mobile edge computing"
    - "efficient multi user computation offloading for mobile edge cloud computing"
    - "user association for load balancing in heterogeneous cellular networks"

Connected through hyperedge HE-3 (induced by source paper "on provisioning cellular networks for distributed inference"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "joint rate and sinr coverage analysis for decoupled uplink downlink biased cell associations in hetnets"

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.IT(Information Theory)