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 "network coding over satcom lessons learned"):
  Abstract: Satellite networks provide unique challenges that can restrict users' quality of service. For example, high packet erasure rates and large latencies can cause significant disruptions to applications such as video streaming or voice-over-IP. Network coding is one promising technique that has been shown to help improve performance, especially in these environments. However, implementing any form of network code can be challenging. This paper will use an example of a generation-based network code and a sliding-window network code to help highlight the benefits and drawbacks of using one over the other. In-order packet delivery delay, as well as network efficiency, will be used as metrics to help differentiate between the two approaches. Furthermore, lessoned learned during the course of our research will be provided in an attempt to help the reader understand when and where network coding provides its benefits.

Includes members:
  Member "low delay random linear coding over a stream":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adaptive causal network coding with feedback")
  Member "fulcrum network codes a code for fluid allocation of complexity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "instantly decodable network coding for real time scalable video broadcast over wireless networks")
  Member "network coding as a wimax link reliability mechanism":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "isn t hybrid arq sufficient")
  Member "speeding multicast by acknowledgment reduction technique smart":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the benefit of limited feedback to generation based random linear network coding in wireless broadcast")
  Member "random linear network coding for time division duplexing when to stop talking and start listening":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "packet loss recovery in broadcast for real time applications in dense wireless networks")

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)