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: "analysis of buffer starvation with application to objective qoe optimization of streaming services"
  Abstract: Our purpose in this paper is to characterize buffer starvations for streaming services. The buffer is modeled as a FIFO queue with exponential service time and Poisson arrivals. When the buffer is empty, the service restarts after a certain amount of packets are prefetched. With this goal, we propose two approaches to obtain exact distribution of the number of buffer starvations, one of which is based on Ballot theorem, and the other uses recursive equations. The Ballot theorem approach gives an explicit result. We extend this approach to the scenario with a constant playback rate using Takacs Ballot theorem. The recursive approach, though not offering an explicit result, allows us to obtain the distribution of starvations with non-independent and identically distributed (i.i.d.) arrival process in which an ON/OFF bursty arrival process is considered. We further compute the starvation probability as a function of the amount of prefetched packets for a large number of files via a fluid analysis. Among many potential applications of starvation analysis, we show how to apply it to optimize objective quality of experience (QoE) of media streaming, by exploiting the tradeoff between startup/rebuffering delay and starvations.

Connected through hyperedge HE-1 (induced by source paper "qoe management of multimedia streaming services in future networks a tutorial and survey"):
  with members:
    - "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges"
    - "a novel qoe aware sdn enabled nfv based management architecture for future multimedia applications on 5g systems"
    - "mptcp meets fec supporting latency sensitive applications over heterogeneous networks"
    - "network slicing for 5g with sdn nfv concepts architectures and challenges"
    - "nfv and sdn key technology enablers for 5g networks"
    - "network slicing to enable scalability and flexibility in 5g mobile networks"
    - "balancing the migration of virtual network functions with replications in data centers"
    - "5g icn delivering icn services over 5g using network slicing"

Connected through hyperedge HE-2 (induced by source paper "fresher content or smoother playback a brownian approximation framework for scheduling real time wireless video streams"):
  with members:
    - "nova qoe driven optimization of dash based video delivery in networks"

Connected through hyperedge HE-3 (induced by source paper "optimal decentralized dynamic policies for video streaming over wireless channels"):
  with members:
    - "optimizing quality of experience of dynamic video streaming over fading wireless networks"

Connected through hyperedge HE-4 (induced by source paper "dynamic adaptive streaming using index based learning algorithms"):
  with members:
    - "index policies for optimal mean variance trade off of inter delivery times in real time sensor networks"
    - "a high reliability asymptotic approach for packet inter delivery time optimization in cyber physical systems"
    - "pathwise performance of debt based policies for wireless networks with hard delay constraints"

Connected through hyperedge HE-5 (induced by source paper "optimizing quality of experience of dynamic video streaming over fading wireless networks"):
  with members:
    - "index policies for optimal mean variance trade off of inter delivery times in real time sensor networks"
    - "decentralized throughput maximizing policies for deadline constrained wireless networks"
    - "a high reliability asymptotic approach for packet inter delivery time optimization in cyber physical systems"
    - "pathwise performance of debt based policies for wireless networks with hard delay constraints"

Connected through hyperedge HE-6 (induced by source paper "computing quality of experience of video streaming in network with long range dependent traffic"):
  with members:
    - "adaptive video streaming for wireless networks with multiple users and helpers"
    - "flow level qoe of video streaming in wireless networks"

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.PF(Performance)