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: "opportunistic network coding for video streaming over wireless"
  Abstract: In this paper, we study video streaming over wireless networks with network coding capabilities. We build upon recent work, which demonstrated that network coding can increase throughput over a broadcast medium, by mixing packets from different flows into a single packet, thus increasing the information content per transmission. Our key insight is that, when the transmitted flows are video streams, network codes should be selected so as to maximize not only the network throughput but also the video quality. We propose video-aware opportunistic network coding schemes that take into account both (i) the decodability of network codes by several receivers and (ii) the importance and deadlines of video packets. Simulation results show that our schemes significantly improve both video quality and throughput.

Connected through hyperedge HE-1 (induced by source paper "packet loss recovery in broadcast for real time applications in dense wireless networks"):
  with members:
    - "on coding for cooperative data exchange"
    - "broadcasting in time division duplexing a random linear network coding approach"
    - "informed network coding for minimum decoding delay"
    - "random linear network coding for time division duplexing when to stop talking and start listening"
    - "random linear network coding a free cipher"

Connected through hyperedge HE-2 (induced by source paper "content aware network coding over device to device networks"):
  with members:
    - "content aware instantly decodable network coding over wireless networks"
    - "completion delay minimization for instantly decodable network codes"
    - "on coding for cooperative data exchange"

Connected through hyperedge HE-3 (induced by source paper "content aware instantly decodable network coding over wireless networks"):
  with members:
    - "completion delay minimization for instantly decodable network codes"
    - "on coding for cooperative data exchange"

Connected through hyperedge HE-4 (induced by source paper "completion delay minimization for instantly decodable network codes"):
  with members:
    - "on the complexity of solving markov decision problems"
    - "multiuser broadcast erasure channel with feedback capacity and algorithms"
    - "coding opportunity densification strategies for instantly decodable network coding"
    - "capacity of 1 to k broadcast packet erasure channels with channel output feedback"
    - "broadcasting in time division duplexing a random linear network coding approach"
    - "effective delay control in online network coding"
    - "feedback based online network coding"
    - "informed network coding for minimum decoding delay"

Connected through hyperedge HE-5 (induced by source paper "coding opportunity densification strategies for instantly decodable network coding"):
  with members:
    - "capacity of 1 to k broadcast packet erasure channels with channel output feedback"
    - "index coding via linear programming"
    - "informed network coding for minimum decoding delay"
    - "online network coding for optimal throughput and delay the three receiver case"

Connected through hyperedge HE-6 (induced by source paper "secure capacity region for erasure broadcast channels with feedback"):
  with members:
    - "multiuser broadcast erasure channel with feedback capacity and algorithms"
    - "wireless network information flow a deterministic approach"
    - "keys through arq theory and practice"
    - "exchanging secrets without using cryptography"
    - "completely stale transmitter channel state information is still very useful"
    - "multiple input multiple output gaussian broadcast channels with common and confidential messages"
    - "the wiretap channel with feedback encryption over the channel"

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)