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: "edgebench benchmarking edge computing platforms"
  Abstract: The emerging trend of edge computing has led several cloud providers to release their own platforms for performing computation at the 'edge' of the network. We compare two such platforms, Amazon AWS Greengrass and Microsoft Azure IoT Edge, using a new benchmark comprising a suite of performance metrics. We also compare the performance of the edge frameworks to cloud-only implementations available in their respective cloud ecosystems. Amazon AWS Greengrass and Azure IoT Edge use different underlying technologies, edge Lambda functions vs. containers, and so we also elaborate on platform features available to developers. Our study shows that both of these edge platforms provide comparable performance, which nevertheless differs in important ways for key types of workloads used in edge applications. Finally, we discuss several current issues and challenges we faced in deploying these platforms.

Connected through hyperedge HE-1 (induced by source paper "performance optimization for edge cloud serverless platforms via dynamic task placement"):
  with members:
    - "serverless computing current trends and open problems"
    - "performance characterization of in memory data analytics on a modern cloud server"

Connected through hyperedge HE-2 (induced by source paper "defog fog computing benchmarks"):
  with members:
    - "cloud benchmarking for maximising performance of scientific applications"
    - "cavbench a benchmark suite for connected and autonomous vehicles"
    - "yolov3 an incremental improvement"
    - "enorm a framework for edge node resource management"
    - "doclite a docker based lightweight cloud benchmarking tool"
    - "challenges and opportunities in edge computing"
    - "container based cloud virtual machine benchmarking"
    - "you only look once unified real time object detection"

Connected through hyperedge HE-3 (induced by source paper "edge aibench towards comprehensive end to end edge computing benchmarking"):
  with members:
    - "aibench an industry standard internet service ai benchmark suite"
    - "federated machine learning concept and applications"
    - "ai benchmark running deep neural networks on android smartphones"
    - "learning the joint representation of heterogeneous temporal events for clinical endpoint prediction"
    - "retain interpretable predictive model in healthcare using reverse time attention mechanism"
    - "deep speech 2 end to end speech recognition in english and mandarin"
    - "facenet a unified embedding for face recognition and clustering"
    - "bigdatabench a big data benchmark suite from internet services"

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)