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 "generalization of lru cache replacement policy with applications to video streaming"):
  Abstract: Caching plays a crucial role in networking systems to reduce the load on the network and has become an ubiquitous functionality available at each router. One of the commonly used mechanisms, Least Recently Used (LRU), works well for identical file sizes. However, for asymmetric file sizes, the performance deteriorates. This paper proposes an adaptation to LRU strategy, called gLRU, where the file is sub-divided into equal-sized chunks. In this strategy, a chunk of the newly requested file is added in the cache, and a chunk of the least-recently-used file is removed from the cache. Even though approximate analysis for the hit rate has been studied for LRU, the analysis does not extend to gLRU since the metric of interest is no longer the hit rate as the cache has partial files. This paper provides a novel approximation analysis for this policy where the cache may have partial file contents. The approximation approach is validated by simulations. Further, gLRU outperforms LRU strategy for Zipf file popularity distribution and censored Pareto file size distribution for the file download times. Video streaming applications can further use the partial cache contents to help the stall durations significantly, and the numerical results indicate significant improvements (29\%) in stall durations using the gLRU strategy as compared to the LRU strategy.

Includes members:
  Member "fastscan robust low complexity rate adaptation algorithm for video streaming over http":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "enhancing video streaming in vehicular networks via resource slicing")
  Member "lbp robust rate adaptation algorithm for svc video streaming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "enhancing video streaming in vehicular networks via resource slicing")
  Member "optimizing tcp loss recovery performance over mobile data networks":
    also connected through other hyperedges:
      (none)
  Member "sprout a functional caching approach to minimize service latency in erasure coded storage":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "capacity of distributed storage systems with clusters and separate nodes")
  Member "impact of traffic mix on caching performance in a content centric network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cache optimization models and algorithms")
  Member "performance evaluation of the random replacement policy for networks of caches":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "caching in the clouds optimized dynamic cache instantiation in content delivery systems")
  Member "a versatile and accurate approximation for lru cache performance":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "online convex optimization for caching networks")

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.NI(Networking and Internet Architecture)