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: "the end of slow networks it s time for a redesign"
  Abstract: Next generation high-performance RDMA-capable networks will require a fundamental rethinking of the design and architecture of modern distributed DBMSs. These systems are commonly designed and optimized under the assumption that the network is the bottleneck: the network is slow and "thin", and thus needs to be avoided as much as possible. Yet this assumption no longer holds true. With InfiniBand FDR 4x, the bandwidth available to transfer data across network is in the same ballpark as the bandwidth of one memory channel, and it increases even further with the most recent EDR standard. Moreover, with the increasing advances of RDMA, the latency improves similarly fast. In this paper, we first argue that the "old" distributed database design is not capable of taking full advantage of the network. Second, we propose architectural redesigns for OLTP, OLAP and advanced analytical frameworks to take better advantage of the improved bandwidth, latency and RDMA capabilities. Finally, for each of the workload categories, we show that remarkable performance improvements can be achieved.

Connected through hyperedge HE-1 (induced by source paper "storm a fast transactional dataplane for remote data structures"):
  with members:
    - "enabling efficient rdma based synchronous mirroring of persistent memory transactions"
    - "datacenter rpcs can be general and fast"

Connected through hyperedge HE-2 (induced by source paper "building atomic crash consistent data stores with disaggregated persistent memory"):
  with members:
    - "the end of a myth distributed transactions can scale"

Connected through hyperedge HE-3 (induced by source paper "datacenter rpcs can be general and fast"):
  with members:
    - "revisiting network support for rdma"
    - "the end of a myth distributed transactions can scale"

Connected through hyperedge HE-4 (induced by source paper "chiller contention centric transaction execution and data partitioning for fast networks"):
  with members:
    - "the end of a myth distributed transactions can scale"

Connected through hyperedge HE-5 (induced by source paper "on smart query routing for distributed graph querying with decoupled storage"):
  with members:
    - "eagr supporting continuous ego centric aggregate queries over large dynamic graphs"
    - "spinner scalable graph partitioning in the cloud"
    - "fast exact shortest path distance queries on large networks by pruned landmark labeling"

Connected through hyperedge HE-6 (induced by source paper "the end of a myth distributed transactions can scale"):
  with members:
    - "on predictive modeling for optimizing transaction execution in parallel oltp systems"
    - "a critique of ansi sql isolation levels"

Connected through hyperedge HE-7 (induced by source paper "top k query processing on encrypted databases with strong security guarantees"):
  with members:
    - "secure k nearest neighbor query over encrypted data in outsourced environments"
    - "optimal aggregation algorithms for middleware"

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)