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: "device to device data storage with regenerating codes"
  Abstract: Caching data files directly on mobile user devices combined with device-to-device (D2D) communications has recently been suggested to improve the capacity of wireless net6works. We investigate the performance of regenerating codes in terms of the total energy consumption of a cellular network. We show that regenerating codes can offer large performance gains. It turns out that using redundancy against storage node failures is only beneficial if the popularity of the data is between certain thresholds. As our major contribution, we investigate under which circumstances regenerating codes with multiple redundant data fragments outdo uncoded caching.

Connected through hyperedge HE-1 (induced by source paper "coded caching clusters with device to device communications"):
  with members:
    - "mobility increases the data offloading ratio in d2d caching networks"
    - "on consideration of content preference and sharing willingness in d2d assisted offloading"
    - "spatially correlated content caching for device to device communications"
    - "fundamentals of cluster centric content placement in cache enabled device to device networks"
    - "optimal geographic caching in finite wireless networks"
    - "wireless device to device caching networks basic principles and system performance"
    - "wireless content caching for small cell and d2d networks"
    - "energy costs for traffic offloading by cache enabled d2d communications"

Connected through hyperedge HE-2 (induced by source paper "on the benefits of edge caching for mimo interference alignment"):
  with members:
    - "optimal geographic caching in cellular networks"
    - "hierarchical coded caching"
    - "performance analysis and optimization for interference alignment over mimo interference channels with limited feedback"
    - "what will 5g be"
    - "living on the edge the role of proactive caching in 5g wireless networks"
    - "cache enabled opportunistic cooperative mimo for video streaming in wireless systems"
    - "many to many matching games for proactive social caching in wireless small cell networks"
    - "csit sharing over finite capacity backhaul for spatial interference alignment"

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)