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: "impact of traffic mix on caching performance in a content centric network"
  Abstract: For a realistic traffic mix, we evaluate the hit rates attained in a two-layer cache hierarchy designed to reduce Internet bandwidth requirements. The model identifies four main types of content, web, file sharing, user generated content and video on demand, distinguished in terms of their traffic shares, their population and object sizes and their popularity distributions. Results demonstrate that caching VoD in access routers offers a highly favorable bandwidth memory tradeoff but that the other types of content would likely be more efficiently handled in very large capacity storage devices in the core. Evaluations are based on a simple approximation for LRU cache performance that proves highly accurate in relevant configurations.

Connected through hyperedge HE-1 (induced by source paper "cache optimization models and algorithms"):
  with members:
    - "learning to cache with no regrets"
    - "introduction to online convex optimization"
    - "cabaret leveraging recommendation systems for mobile edge caching"
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "competitive caching with machine learned advice"
    - "online convex optimization and no regret learning algorithms guarantees and applications"
    - "show me the cache optimizing cache friendly recommendations for sequential content access"
    - "a reinforcement learning approach to proactive caching in wireless networks"

Connected through hyperedge HE-2 (induced by source paper "learning to cache with no regrets"):
  with members:
    - "optimal and scalable caching for 5g using reinforcement learning of space time popularities"
    - "competitive caching with machine learned advice"
    - "online convex optimization and no regret learning algorithms guarantees and applications"
    - "a reinforcement learning approach to proactive caching in wireless networks"
    - "jointly optimal routing and caching for arbitrary network topologies"
    - "spatial multi lru distributed caching for wireless networks with coverage overlaps"
    - "placing dynamic content in caches with small population"
    - "optimal geographic caching in cellular networks"

Connected through hyperedge HE-3 (induced by source paper "resource pooling in large scale content delivery systems"):
  with members:
    - "effects of storage heterogeneity in distributed cache systems"
    - "content replication in large distributed caches"
    - "order optimal rate of caching and coded multicasting with random demands"
    - "coded caching for multi level popularity and access"
    - "serving content with unknown demand the high dimensional regime"
    - "multi level coded caching"
    - "online coded caching"
    - "coded caching with nonuniform demands"

Connected through hyperedge HE-4 (induced by source paper "generalization of lru cache replacement policy with applications to video streaming"):
  with members:
    - "fastscan robust low complexity rate adaptation algorithm for video streaming over http"
    - "lbp robust rate adaptation algorithm for svc video streaming"
    - "optimizing tcp loss recovery performance over mobile data networks"
    - "sprout a functional caching approach to minimize service latency in erasure coded storage"
    - "performance evaluation of the random replacement policy for networks of caches"
    - "a versatile and accurate approximation for lru cache performance"

Connected through hyperedge HE-5 (induced by source paper "effects of storage heterogeneity in distributed cache systems"):
  with members:
    - "resource pooling in large scale content delivery systems"
    - "cache aided heterogeneous networks coverage and delay analysis"
    - "content replication in large distributed caches"
    - "hierarchical coded caching"
    - "fundamental limits of caching"

Connected through hyperedge HE-6 (induced by source paper "asymptotic miss ratio of lru caching with consistent hashing"):
  with members:
    - "on resource pooling and separation for lru caching"
    - "approximation of lru caches miss rate application to power law popularities"
    - "adaptive caching networks with optimality guarantees"
    - "exploring the memory bandwidth tradeoff in an information centric network"
    - "a versatile and accurate approximation for lru cache performance"

Connected through hyperedge HE-7 (induced by source paper "a low complexity approach to distributed cooperative caching with geographic constraints"):
  with members:
    - "delivery latency regions in fog rans with edge caching and cloud processing"
    - "spatial multi lru caching for wireless networks with coverage overlaps"
    - "a stackelberg game for incentive proactive caching mechanisms in wireless networks"
    - "cloud and cache aided wireless networks fundamental latency trade offs"
    - "a utility optimization approach to network cache design"
    - "optimal geographic caching in cellular networks"
    - "fundamental limits of cache aided wireless bc interplay of coded caching and csit feedback"
    - "cache aided interference channels"

Connected through hyperedge HE-8 (induced by source paper "adaptive ttl based caching for content delivery"):
  with members:
    - "accurate learning or fast mixing dynamic adaptability of caching algorithms"
    - "a utility optimization approach to network cache design"
    - "an inverse problem approach for content popularity estimation"
    - "least recently used caches under the shot noise model"
    - "catalog dynamics impact of content publishing and perishing on the performance of a lru cache"
    - "a unified approach to the performance analysis of caching systems"
    - "a versatile and accurate approximation for lru cache performance"

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)