human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "constant time updates in hierarchical heavy hitters"):
  Abstract: Monitoring tasks, such as anomaly and DDoS detection, require identifying frequent flow aggregates based on common IP prefixes. These are known as hierarchical heavy hitters (HHH), where the hierarchy is determined based on the type of prefixes of interest in a given application. The per packet complexity of existing HHH algorithms is proportional to the size of the hierarchy, imposing significant overheads.   In this paper, we propose a randomized constant time algorithm for HHH. We prove probabilistic precision bounds backed by an empirical evaluation. Using four real Internet packet traces, we demonstrate that our algorithm indeed obtains comparable accuracy and recall as previous works, while running up to 62 times faster. Finally, we extended Open vSwitch (OVS) with our algorithm and showed it is able to handle 13.8 million packets per second. In contrast, incorporating previous works in OVS only obtained 2.5 times lower throughput.

Includes members:
  Member "optimal elephant flow detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a fast and compact invertible sketch for network wide heavy flow detection")
  Member "heavy hitter detection entirely in the data plane":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "constellation a high performance geo distributed middlebox framework")
  Member "randomized admission policy for efficient top k and frequency estimation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a fast and compact invertible sketch for network wide heavy flow detection")
  Member "moongen a scriptable high speed packet generator":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "me love syn cookies syn flood mitigation in programmable data planes")
  Member "tinylfu a highly efficient cache admission policy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a hybrid cache architecture for meeting per tenant performance goals in a private cloud")
  Member "hierarchical heavy hitters with the space saving algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "memory efficient performance monitoring on programmable switches with lean algorithms")

Question: Please tell me which class the source paper 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.DS(Data Structures and Algorithms)