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: "backhaul traffic balancing and dynamic content centric clustering for the downlink of fog radio access network"
  Abstract: Recently, an evolution of the Cloud Radio Access Network (C-RAN) has been proposed, named as Fog Radio Access Network (F-RAN). Compared to C-RAN, the Radio Units (RUs) in F-CAN are equipped with local caches, which can store some frequently requested files. In the downlink, users requesting the same file form a multicast group, and are cooperatively served by a cluster of RUs. The requested file is either available locally in the cache of this cluster or fetched from the Central Processor (CP) via backhauls. Thus caching some frequently requested files can greatly reduce the burden on backhaul links. Whether a specific RU should be involved in a cluster to serve a multicast group depends on its backhaul capacity, requested files, cached files and the channel. Therefore it is subject to optimization. In this paper we investigate the joint design of multicast beamforming, dynamic clustering and backhaul traffic balancing. Beamforming and clustering are jointly optimized in order to minimize the power consumed, while QoS of each user is to be met and the traffic on each backhaul link is balanced according to its capacity.

Connected through hyperedge HE-1 (induced by source paper "fundamental limits on delivery time in cloud and cache aided heterogeneous networks"):
  with members:
    - "fundamental tradeoff between storage and latency in cache aided wireless interference networks"
    - "degrees of freedom of cache aided wireless interference networks"
    - "fundamental limits of cache aided interference management"
    - "coded caching for a large number of users"
    - "fog computing based radio access networks issues and challenges"
    - "joint optimization of cloud and edge processing for fog radio access networks"
    - "content centric sparse multicast beamforming for cache enabled cloud ran"
    - "cooperation for interference management a gdof perspective"

Connected through hyperedge HE-2 (induced by source paper "a comprehensive survey on fog computing state of the art and research challenges"):
  with members:
    - "coding for distributed fog computing"
    - "realizing the tactile internet haptic communications over next generation 5g cellular networks"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "fog computing based radio access networks issues and challenges"
    - "fit a fog computing device for speech teletreatments"
    - "analysis of an offloading scheme for data centers in the framework of fog computing"
    - "fog data enhancing telehealth big data through fog computing"
    - "the emerging internet of things marketplace from an industrial perspective a survey"

Connected through hyperedge HE-3 (induced by source paper "echo state networks for proactive caching in cloud based radio access networks with mobile users"):
  with members:
    - "echo state networks for self organizing resource allocation in lte u with uplink downlink decoupling"
    - "joint millimeter wave fronthaul and ofdma resource allocation in ultra dense cran"
    - "optimal fronthaul quantization for cloud radio positioning"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "octopus a cooperative hierarchical caching strategy for cloud radio access networks"
    - "joint wireless fronthaul and ofdma resource allocation in ultra dense cran"
    - "mobility aware caching for content centric wireless networks modeling and methodology"
    - "cluster content caching an energy efficient approach to improve quality of service in cloud radio access networks"

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)