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: "communications caching and computing for mobile virtual reality modeling and tradeoff"
  Abstract: Virtual reality (VR) over wireless is emerging as an important use case of 5G networks. Immersive VR experience requires the delivery of huge data at ultra-low latency, thus demanding ultra-high transmission rate. This challenge can be largely addressed by the recent network architecture known as mobile edge computing (MEC), which enables caching and computing capabilities at the edge of wireless networks. This paper presents a novel MEC-based mobile VR delivery framework that is able to cache parts of the field of views (FOVs) in advance and run certain post-processing procedures at the mobile VR device. To optimize resource allocation at the mobile VR device, we formulate a joint caching and computing decision problem to minimize the average required transmission rate while meeting a given latency constraint. When FOVs are homogeneous, we obtain a closed-form expression for the optimal joint policy which reveals interesting communications-caching-computing tradeoffs. When FOVs are heterogeneous, we obtain a local optima of the problem by transforming it into a linearly constrained indefinite quadratic problem then applying concave convex procedure. Numerical results demonstrate great promises of the proposed mobile VR delivery framework in saving communication bandwidth while meeting low latency requirement.

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"
    - "minimizing latency to support vr social interactions over wireless cellular systems via bandwidth allocation"
    - "optimized base station cache allocation for cloud radio access network with multicast backhaul"
    - "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 "communications caching computing tradeoff analysis for bidirectional data computation in mobile edge networks"):
  with members:
    - "bandwidth gain from mobile edge computing and caching in wireless multicast systems"
    - "a survey on mobile edge computing the communication perspective"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "joint pushing and caching for bandwidth utilization maximization in wireless networks"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "the three primary colors of mobile systems"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "power delay tradeoff in multi user mobile edge computing systems"

Connected through hyperedge HE-3 (induced by source paper "prediction communication and computing duration optimization for vr video streaming"):
  with members:
    - "predicting head movement in panoramic video a deep reinforcement learning approach"
    - "very long term field of view prediction for 360 degree video streaming"
    - "optimal multicast of tiled 360 vr video in ofdma systems"
    - "a survey on mobile edge computing the communication perspective"
    - "virtual reality over wireless networks quality of service model and learning based resource management"
    - "adaptive 360 vr video streaming divide and conquer"

Connected through hyperedge HE-4 (induced by source paper "a view on edge caching applications"):
  with members:
    - "the rich prefetching in edge caches for in order delivery to connected cars"
    - "smart edge cocaco ai enabled smart edge with joint computation caching and communication in heterogeneous iot"
    - "air ground integrated vehicular network slicing with content pushing and caching"
    - "caching aided collaborative d2d operation for predictive data dissemination in industrial iot"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "fog computing in medical internet of things architecture implementation and applications"

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)