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: "joint optimization of qoe and fairness through network assisted adaptive mobile video streaming"
  Abstract: MPEG has recently proposed Server and Network Assisted Dynamic Adaptive Streaming over HTTP (SAND-DASH) for video streaming over the Internet. In contrast to the purely client-based video streaming in which each client makes its own decision to adjust its bitrate, SAND-DASH enables a group of simultaneous clients to select their bitrates in a coordinated fashion in order to improve resource utilization and quality of experience. In this paper, we study the performance of such an adaptation strategy compared to the traditional approach with large number of clients having mobile Internet access. We propose a multi-servers multi-coordinators (MSs-MCs) framework to model groups of remote clients accessing video content replicated to spatially distributed edge servers. We then formulate an optimization problem to maximize jointly the QoE of individual clients, proportional fairness in allocating the limited resources of base stations as well as balancing the utilized resources among multiple serves. We then present an efficient heuristic-based solution to the problem and perform simulations in order to explore parameter space of the scheme as well as to compare the performance to purely client-based DASH.

Connected through hyperedge HE-1 (induced by source paper "optimal network assisted multi user dash video streaming"):
  with members:
    - "adaptive video streaming for wireless networks with multiple users and helpers"
    - "probe and adapt rate adaptation for http video streaming at scale"
    - "nova qoe driven optimization of dash based video delivery in 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.MM(Multimedia)