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: "caching at the wireless edge design aspects challenges and future directions"
  Abstract: Caching at the wireless edge is a promising way to boost spectral efficiency and reduce energy consumption of wireless systems. These improvements are rooted in the fact that popular contents are reused, asynchronously, by many users. In this article we first introduce methods to predict the popularity distributions and user preferences, and the impact of erroneous information. We then discuss the two aspects of caching systems, content placement and delivery. We expound the key differences between wired and wireless caching, and outline the differences in the system arising from where the caching takes place (e.g., at base stations or on the wireless devices themselves). Special attention is paid to the essential limitations in wireless caching, and possible trade-offs between spectral efficiency, energy efficiency, and cache size.

Connected through hyperedge HE-1 (induced by source paper "enhancing physical layer security of random caching in large scale multi antenna heterogeneous wireless networks"):
  with members:
    - "secure and energy efficient transmissions in cache enabled heterogeneous cellular networks performance analysis and optimization"
    - "enhancing performance of random caching in large scale wireless networks with multiple receive antennas"
    - "physical layer security in cache enabled cooperative small cell networks against randomly distributed eavesdroppers"
    - "a unified framework for the tractable analysis of multi antenna wireless networks"
    - "enhancing performance of random caching in large scale heterogeneous wireless networks with random discontinuous transmission"
    - "delivery secrecy tradeoff for cache enabled stochastic networks content placement optimization"
    - "random caching based cooperative transmission in heterogeneous wireless networks"
    - "optimal content placement for offloading in cache enabled heterogeneous wireless networks"

Connected through hyperedge HE-2 (induced by source paper "caching at base stations with multi cluster multicast wireless backhaul via accelerated first order algorithm"):
  with members:
    - "caching at base stations with heterogeneous user demands and spatial locality"
    - "optimized base station cache allocation for cloud radio access network with multicast backhaul"
    - "modeling analysis and optimization of coded caching in small cell networks"
    - "noisy broadcast networks with receiver caching"
    - "content centric sparse multicast beamforming for cache enabled cloud ran"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "cloud radio access networks with coded caching"
    - "analysis and optimization of caching and multicasting in large scale cache enabled wireless networks"

Connected through hyperedge HE-3 (induced by source paper "viewport aware deep reinforcement learning approach for 360 o video caching"):
  with members:
    - "applications of deep reinforcement learning in communications and networking a survey"
    - "cost effective cache deployment in mobile heterogeneous networks"
    - "saltinet scan path prediction on 360 degree images using saliency volumes"
    - "edge caching wireless networks performance analysis and optimization"
    - "deep reinforcement learning framework applications and embedded implementations"
    - "a deep reinforcement learning based framework for content caching"
    - "context aware proactive content caching with service differentiation in wireless networks"
    - "deep reinforcement learning in large discrete action spaces"

Connected through hyperedge HE-4 (induced by source paper "pa cache learning based popularity aware content caching in edge networks"):
  with members:
    - "deep reinforcement learning for adaptive caching in hierarchical content delivery networks"
    - "online deep learning learning deep neural networks on the fly"
    - "what when and where to cache a unified optimization approach"
    - "optimizing timer based policies for general cache networks"
    - "understanding performance of edge content caching for mobile video streaming"
    - "fractalnet ultra deep neural networks without residuals"
    - "mxnet a flexible and efficient machine learning library for heterogeneous distributed systems"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-5 (induced by source paper "consistent user traffic allocation and load balancing in mobile edge caching"):
  with members:
    - "utilcache effectively and practicably reducing link cost in information centric network"
    - "optimal cache leasing from a mobile network operator to a content provider"
    - "joint caching routing and channel assignment for collaborative small cell cellular networks"
    - "on the complexity of optimal routing and content caching in heterogeneous networks"

Connected through hyperedge HE-6 (induced by source paper "individual preference aware caching policy design in wireless d2d networks"):
  with members:
    - "throughput outage analysis and evaluation of cache aided d2d networks with measured popularity distributions"
    - "modeling and performance analysis of full duplex communications in cache enabled d2d networks"
    - "learning based delay aware caching in wireless d2d caching networks"
    - "caching policy optimization for d2d communications by learning user preference"
    - "high throughput opportunistic cooperative device to device communications with caching"
    - "cache enabled device to device communications offloading gain and energy cost"
    - "on consideration of content preference and sharing willingness in d2d assisted offloading"
    - "optimizing content caching to maximize the density of successful receptions in device to device networking"

Connected through hyperedge HE-7 (induced by source paper "modeling and performance analysis in cache enabled millimeter wave hetnets with access and backhaul integration"):
  with members:
    - "modeling and analysis of d2d millimeter wave networks with poisson cluster processes"
    - "a unified asymptotic analysis of area spectral efficiency in ultradense cellular networks"
    - "downlink cellular network analysis with los nlos propagation and elevated base stations"
    - "modeling analysis and optimization of coded caching in small cell networks"
    - "dense small cell networks from noise limited to dense interference limited"
    - "coverage in downlink heterogeneous mmwave cellular networks with user centric small cell deployment"
    - "energy efficiency of downlink networks with caching at base stations"
    - "fundamentals of the downlink green coverage and energy efficiency in heterogeneous networks"

Connected through hyperedge HE-8 (induced by source paper "on the effective throughput of coded caching a game theoretic perspective"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "energy efficiency gains of caching for interference channels"
    - "caching meets millimeter wave communications for enhanced mobility management in 5g networks"
    - "on coded caching in the overloaded miso broadcast channel"
    - "a survey on low latency towards 5g ran core network and caching solutions"
    - "cost optimal caching for d2d networks with user mobility modeling analysis and computational approaches"
    - "a stackelberg game for incentive proactive caching mechanisms in wireless networks"
    - "private coded caching"

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.NI(Networking and Internet Architecture)