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: "benchmarking fast data platforms for the aadhaar biometric database"
  Abstract: Aadhaar is the world’s largest biometric database with a billion records, being compiled as an identity platform to deliver social services to residents of India. Aadhaar processes streams of biometric data as residents are enrolled and updated. Besides \(\sim \)1 million enrollments and updates per day, up to 100 million daily biometric authentications are expected during delivery of various public services. These form critical Big Data applications, with large volumes and high velocity of data. Here, we propose a stream processing workload, based on the Aadhaar enrollment and Authentication applications, as a Big Data benchmark for distributed stream processing systems. We describe the application composition, and characterize their task latencies and selectivity, and data rate and size distributions, based on real observations. We also validate this benchmark on Apache Storm using synthetic streams and simulated application logic. This paper offers a unique glimpse into an operational national identity infrastructure, and proposes a benchmark for “fast data” platforms to support such eGovernance applications.

Connected through hyperedge HE-1 (induced by source paper "model driven scheduling for distributed stream processing systems"):
  with members:
    - "benchmarking distributed stream processing platforms for iot applications"
    - "task allocation for distributed stream processing"
    - "r storm resource aware scheduling in storm"
    - "drs dynamic resource scheduling for real time analytics over fast streams"
    - "bigdatabench a big data benchmark suite from internet services"
    - "internet of things iot a vision architectural elements and future directions"

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.DC(Distributed, Parallel, and Cluster Computing)