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: "a general tractable and accurate model for a cascade of caches"
  Abstract: Performance evaluation of caching systems is an old and widely investigated research topic. The research community is once again actively working on this topic because the Internet is evolving towards new transfer modes, which envisage to cache both contents and instructions within the network. In particular, there is interest in characterizing multi-cache systems, in which requests not satisfied by a cache are forwarded to other caches. #R##N#In this field, this paper contributes as follows. First, we devise a simple but accurate approximate analysis for caches fed by general "renewal" traffic patterns. Second, we characterize and model the traffic statistics for the output (miss) stream. Third, we show in the simple example case of tandem caches how the resulting output stream model can be conveniently exploited to analyze the performance of subsequent cache stages. The main novelty of our work stems in the ability to handle traffic patterns beyond the traditional independent reference model, thus permitting simple assessment of cascade of caches as well as improved understanding of the phenomena involved in cache hierarchies.

Connected through hyperedge HE-1 (induced by source paper "q caching an integrated reinforcement learning approach for caching and routing in information centric networks"):
  with members:
    - "a utility optimization approach to network cache design"
    - "enabling correct interest forwarding and retransmissions in a content centric network"
    - "enabling information centric networks through opportunistic search routing and caching"

Connected through hyperedge HE-2 (induced by source paper "flexible content placement in cache networks using reinforced counters"):
  with members:
    - "exact analysis of ttl cache networks the case of caching policies driven by stopping times"
    - "enabling information centric networks through opportunistic search routing and caching"

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.NI(Networking and Internet Architecture)