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: "asymptotic laws for joint content replication and delivery in wireless networks"
  Abstract: We investigate the scalability of multihop wireless communications, a major concern in networking, for the case that users access content replicated across the nodes. In contrast to the standard paradigm of randomly selected communicating pairs, content replication is efficient for certain regimes of file popularity, cache, and network size. Our study begins with the detailed joint content replication and delivery problem on a 2-D square grid, a hard combinatorial optimization. This is reduced to a simpler problem based on replication density, whose performance is of the same order as the original. Assuming a Zipf popularity law, and letting the size of content and network both go to infinity, we identify the scaling laws and regimes of the required link capacity, ranging from O(√N) down to O(1) .

Connected through hyperedge HE-1 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks"):
  with members:
    - "spectrum sharing in vehicular networks based on multi agent reinforcement learning"
    - "deep learning based channel estimation for massive mimo with mixed resolution adcs"
    - "deep learning based wireless resource allocation with application to vehicular networks"
    - "using grouped linear prediction and accelerated reinforcement learning for online content caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "multi agent learning for cooperative large scale caching networks"
    - "deep reinforcement learning based resource allocation for v2v communications"
    - "random caching based cooperative transmission in 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"
    - "caching at the wireless edge design aspects challenges and future directions"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "cache optimization models and algorithms"):
  with members:
    - "learning to cache with no regrets"
    - "introduction to online convex optimization"
    - "cabaret leveraging recommendation systems for mobile edge caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "competitive caching with machine learned advice"
    - "online convex optimization and no regret learning algorithms guarantees and applications"
    - "show me the cache optimizing cache friendly recommendations for sequential content access"
    - "a reinforcement learning approach to proactive caching in wireless networks"

Connected through hyperedge HE-4 (induced by source paper "optimal caching designs for perfect imperfect and unknown file popularity distributions in large scale multi tier wireless networks"):
  with members:
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "random caching based cooperative transmission in heterogeneous wireless networks"
    - "a deep reinforcement learning based framework for content caching"
    - "caching policy for cache enabled d2d communications by learning user preference"
    - "a learning based approach to caching in heterogenous small cell networks"
    - "optimization and analysis of probabilistic caching in n tier heterogeneous networks"
    - "analysis and optimization of caching and multicasting in large scale cache enabled heterogeneous wireless networks"
    - "cooperative caching and transmission design in cluster centric small cell networks"

Connected through hyperedge HE-5 (induced by source paper "optimized base station cache allocation for cloud radio access network with multicast backhaul"):
  with members:
    - "fog aided wireless networks for content delivery fundamental latency tradeoffs"
    - "fundamental tradeoff between storage and latency in cache aided wireless interference networks"
    - "modeling analysis and optimization of coded caching in small cell networks"
    - "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"
    - "sparse beamforming and user centric clustering for downlink cloud radio access network"

Connected through hyperedge HE-6 (induced by source paper "on the effects of subpacketization in content centric mobile networks"):
  with members:
    - "information theoretic caching the multi user case"
    - "wireless device to device caching networks basic principles and system performance"
    - "optimizing mds codes for caching at the edge"
    - "fundamental limits of caching in wireless d2d networks"
    - "parallel opportunistic routing in wireless networks"
    - "the throughput outage tradeoff of wireless one hop caching networks"
    - "decentralized coded caching attains order optimal memory rate tradeoff"
    - "fundamental limits of caching"

Connected through hyperedge HE-7 (induced by source paper "network decomposed hierarchical cooperation in ad hoc networks with social relationships"):
  with members:
    - "on the effects of subpacketization in content centric mobile networks"
    - "leveraging social communities for optimizing cellular device to device communications"
    - "context aware small cell networks how social metrics improve wireless resource allocation"
    - "parallel opportunistic routing in wireless networks"
    - "improved capacity scaling in wireless networks with infrastructure"
    - "capacity scaling of wireless ad hoc networks shannon meets maxwell"
    - "on capacity scaling in arbitrary wireless networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-8 (induced by source paper "stability and dynamic control of underlay mobile edge networks"):
  with members:
    - "wireless device to device caching networks basic principles and system performance"
    - "cognitive radio networks with probabilistic relaying stable throughput and delay tradeoffs"

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)