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: "parallel index based stream join on a multicore cpu"
  Abstract: There is increasing interest in using multicore processors to accelerate stream processing. For example, indexing sliding window content to enhance the performance of streaming queries is greatly improved by utilizing the computational capabilities of a multicore processor. However, designing an effective concurrency control mechanism that addresses the problem of concurrent indexing in highly dynamic settings remains a challenge. In this paper, we introduce an index data structure, called the Partitioned In-memory Merge-Tree, to address the challenges that arise when indexing highly dynamic data, which are common in streaming settings. To complement the index, we design an algorithm to realize a parallel index-based stream join that exploits the computational power of multicore processors. Our experiments using an octa-core processor show that our parallel stream join achieves up to 5.5 times higher throughput than a single-threaded approach.

Connected through hyperedge HE-1 (induced by source paper "hardware conscious stream processing a survey"):
  with members:
    - "briskstream scaling data stream processing on shared memory multicore architectures"
    - "streambox hbm stream analytics on high bandwidth hybrid memory"
    - "join query optimization techniques for complex event processing applications"
    - "panjoin a partition based adaptive stream join"
    - "a survey of state management in big data processing systems"
    - "serverless computing current trends and open problems"
    - "ingestion indexing and retrieval of high velocity multidimensional sensor data on a single node"
    - "the end of a myth distributed transactions can scale"

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.DB(Databases)