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: "minimizing latency to support vr social interactions over wireless cellular systems via bandwidth allocation"
  Abstract: Immersive social interactions of mobile users are soon to be enabled within a virtual space, by means of virtual reality (VR) technologies and wireless cellular systems. In a VR mobile social network, the states of all interacting users should be updated synchronously and with low latency via two-way communications with edge computing servers. The resulting end-to-end latency depends on the relationship between the virtual and physical locations of the wireless VR users and of the edge servers. In this work, the problem of analyzing and optimizing the end-to-end latency is investigated for a simple network topology, yielding important insights into the interplay between physical and virtual geometries.

Connected through hyperedge HE-1 (induced by source paper "mobile communications computing and caching resources optimization for coded caching with device computing"):
  with members:
    - "bandwidth gain from mobile edge computing and caching in wireless multicast systems"
    - "optimized base station cache allocation for cloud radio access network with multicast backhaul"
    - "communications caching and computing for mobile virtual reality modeling and tradeoff"
    - "edge computing meets millimeter wave enabled vr paving the way to cutting the cord"
    - "coded caching with distributed storage"
    - "the three primary colors of mobile systems"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "optimization and analysis of probabilistic caching in n tier heterogeneous networks"

Connected through hyperedge HE-2 (induced by source paper "wireless edge computing with latency and reliability guarantees"):
  with members:
    - "distributed federated learning for ultra reliable low latency vehicular communications"
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "how reliable and capable is multi connectivity"
    - "a tutorial on beam management for 3gpp nr at mmwave frequencies"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "coded federated computing in wireless networks with straggling devices and imperfect csi"
    - "ultra reliable communication in 5g mmwave networks a risk sensitive approach"
    - "on device federated learning via blockchain and its latency analysis"

Connected through hyperedge HE-3 (induced by source paper "one pixel image and rf signal based split learning for mmwave received power prediction"):
  with members:
    - "proactive received power prediction using machine learning and depth images for mmwave networks"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "tractable resource management with uplink decoupled millimeter wave overlay in ultra dense cellular networks"

Connected through hyperedge HE-4 (induced by source paper "urllc embb slicing to support vr multimodal perceptions over wireless cellular systems"):
  with members:
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "toward low latency and ultra reliable virtual reality"
    - "towards 5g enabled tactile robotic telesurgery"
    - "revisiting frequency reuse towards supporting ultra reliable ubiquitous rate communication"
    - "coverage and rate of downlink sequence transmissions with reliability guarantees"
    - "energy efficient resource allocation for mobile edge computing based augmented reality applications"
    - "tractable resource management with uplink decoupled millimeter wave overlay in ultra dense cellular networks"
    - "user centric mobility management in ultra dense cellular networks under spatio temporal dynamics"

Connected through hyperedge HE-5 (induced by source paper "energy efficient mobile edge computation offloading for applications with shared data"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "echo state transfer learning for data correlation aware resource allocation in wireless virtual reality"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "energy efficient resource allocation for mobile edge computing based augmented reality applications"
    - "decentralized computation offloading game for mobile cloud computing"
    - "energy efficient mobile cloud computing powered by wireless energy transfer"

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)