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: "performance bound analysis for crowdsourced mobile video streaming"
  Abstract: Adaptive bitrate (ABR) streaming enables video users to adapt the playing bitrate to the real-time network conditions to achieve the desirable quality of experience (QoE). In this work, we propose a novel crowdsourced streaming framework for multi-user ABR video streaming over wireless networks. This framework enables the nearby mobile video users to crowdsource their radio links and resources for cooperative video streaming. We focus on analyzing the social welfare performance bound of the proposed crowdsourced streaming system. Directly solving this bound is challenging due to the asynchronous operations of users. To this end, we introduce a virtual time-slotted system with the synchronized operations, and formulate the associated social welfare optimization problem as a linear programming. We show that the optimal social welfare performance of the virtual system provides effective upper-bound and lower-bound for the optimal performance (bound) of the original asynchronous system, hence characterizes the feasible performance region of the proposed crowdsourced streaming system. The performance bounds derived in this work can serve as a benchmark for the future online algorithm design and incentive mechanism design.

Connected through hyperedge HE-1 (induced by source paper "multi user cooperative mobile video streaming performance analysis and online mechanism design"):
  with members:
    - "data centric mobile crowdsensing"
    - "sustainable incentives for mobile crowdsensing auctions lotteries and trust and reputation systems"
    - "probe and adapt rate adaptation for http video streaming at scale"
    - "base station assisted device to device communications for high throughput wireless video networks"

Connected through hyperedge HE-2 (induced by source paper "when data sponsoring meets edge caching a game theoretic analysis"):
  with members:
    - "joint optimization of data sponsoring and edge caching for mobile video delivery"
    - "efficient and fair collaborative mobile internet access"
    - "mine gold to deliver green cognitive communications"
    - "bargaining based mobile data offloading"

Connected through hyperedge HE-3 (induced by source paper "multi dimensional auction mechanisms for crowdsourced mobile video streaming"):
  with members:
    - "bola near optimal bitrate adaptation for online videos"
    - "incentivizing sharing in realtime d2d streaming networks a mean field game perspective"
    - "probe and adapt rate adaptation for http video streaming at scale"

Connected through hyperedge HE-4 (induced by source paper "joint optimization of data sponsoring and edge caching for mobile video delivery"):
  with members:
    - "providing long term participation incentive in participatory sensing"
    - "bargaining based mobile data offloading"
    - "a survey of smart data pricing past proposals current plans and future trends"

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)