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: "tinylfu a highly efficient cache admission policy"
  Abstract: This paper proposes to use a frequency based cache admission policy in order to boost the effectiveness of caches subject to skewed access distributions. Given a newly accessed item and an eviction candidate from the cache, our scheme decides, based on the recent access history, whether it is worth admitting the new item into the cache at the expense of the eviction candidate. #R##N#Realizing this concept is enabled through a novel approximate LFU structure called TinyLFU, which maintains an approximate representation of the access frequency of a large sample of recently accessed items. TinyLFU is very compact and light-weight as it builds upon Bloom filter theory. #R##N#We study the properties of TinyLFU through simulations of both synthetic workloads as well as multiple real traces from several sources. These simulations demonstrate the performance boost obtained by enhancing various replacement policies with the TinyLFU eviction policy. Also, a new combined replacement and eviction policy scheme nicknamed W-TinyLFU is presented. W-TinyLFU is demonstrated to obtain equal or better hit-ratios than other state of the art replacement policies on these traces. It is the only scheme to obtain such good results on all traces.

Connected through hyperedge HE-1 (induced by source paper "a hybrid cache architecture for meeting per tenant performance goals in a private cloud"):
  with members:
    - "learning based dynamic cache management in a cloud"

Connected through hyperedge HE-2 (induced by source paper "practical bounds on optimal caching with variable object sizes"):
  with members:
    - "adaptive caching networks with optimality guarantees"
    - "general caching is hard even with small pages"
    - "a nearly linear time ptas for explicit fractional packing and covering linear programs"
    - "exact analysis of ttl cache networks the case of caching policies driven by stopping times"
    - "a combinatorial tilde o m 3 2 time algorithm for the min cost flow problem"
    - "a unified approach to the performance analysis of caching systems"
    - "performance evaluation of the random replacement policy for networks of caches"
    - "a versatile and accurate approximation for lru cache performance"

Connected through hyperedge HE-3 (induced by source paper "fast flow volume estimation"):
  with members:
    - "optimal elephant flow detection"
    - "a high performance algorithm for identifying frequent items in data streams"
    - "constant time updates in hierarchical heavy hitters"
    - "heavy hitter detection entirely in the data plane"
    - "randomized admission policy for efficient top k and frequency estimation"
    - "hierarchical heavy hitters with the space saving algorithm"

Connected through hyperedge HE-4 (induced by source paper "constant time updates in hierarchical heavy hitters"):
  with members:
    - "optimal elephant flow detection"
    - "heavy hitter detection entirely in the data plane"
    - "randomized admission policy for efficient top k and frequency estimation"
    - "moongen a scriptable high speed packet generator"
    - "hierarchical heavy hitters with the space saving algorithm"

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.OS(Operating Systems)