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 "optimized video streaming over cloud a stall quality trade off"):
  Abstract: As video-streaming services have expanded and improved, cloud-based video has evolved into a necessary feature of any successful business for reaching internal and external audiences. In this paper, video streaming over distributed storage is considered where the video segments are encoded using an erasure code for better reliability. There are multiple parallel streams between each server and the edge router. For each client request, we need to determine the subset of servers to get the data, as well as one of the parallel stream from each chosen server. In order to have this scheduling, this paper proposes a two-stage probabilistic scheduling. The selection of video quality is also chosen with a certain probability distribution. With these parameters, the playback time of video segments is determined by characterizing the download time of each coded chunk for each video segment. Using the playback times, a bound on the moment generating function of the stall duration is used to bound the mean stall duration. Based on this, we formulate an optimization problem to jointly optimize the convex combination of mean stall duration and average video quality for all requests, where the two-stage probabilistic scheduling, probabilistic video quality selection, bandwidth split among parallel streams, and auxiliary bound parameters can be chosen. This non-convex problem is solved using an efficient iterative algorithm. Evaluation results show significant improvement in QoE metrics for cloud-based video as compared to the considered baselines.

Includes members:
  Member "video streaming in distributed erasure coded storage systems stall duration analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capacity of distributed storage systems with clusters and separate nodes")
  Member "parallel and distributed methods for nonconvex optimization part i theory":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimization of massive full dimensional mimo for positioning and communication")
  Member "when queueing meets coding optimal latency data retrieving scheme in storage clouds":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "delay optimal policies in partial fork join systems with redundancy and random slowdowns")
  Member "xoring elephants novel erasure codes for big data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on optimal locally repairable codes and generalized sector disk codes")
  Member "on the delay storage trade off in content download from coded distributed storage systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a combinatorial view of the service rates of codes problem its equivalence to fractional matching and its connection with batch codes")
  Member "the mds queue analysing the latency performance of erasure codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a combinatorial view of the service rates of codes problem its equivalence to fractional matching and its connection with batch codes")

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)