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: "coded network function virtualization fault tolerance via in network coding"
  Abstract: Network function virtualization (NFV) prescribes the instantiation of network functions on general-purpose network devices, such as servers and switches. While yielding a more flexible and cost-effective network architecture, NFV is potentially limited by the fact that commercial off-the-shelf hardware is less reliable than the dedicated network elements used in conventional cellular deployments. The typical solution for this problem is to duplicate network functions across geographically distributed hardware in order to ensure diversity. In contrast, this letter proposes to leverage channel coding in order to enhance the robustness on NFV to hardware failure. The proposed approach targets the network function of uplink channel decoding, and builds on the algebraic structure of the encoded data frames in order to perform in-network coding on the signals to be processed at different servers. The key principles underlying the proposed coded NFV approach are presented for a simple embodiment and extensions are discussed. Numerical results demonstrate the potential gains obtained with the proposed scheme as compared to the conventional diversity-based fault-tolerant scheme in terms of error probability.

Connected through hyperedge HE-1 (induced by source paper "optimum transmission delay for function computation in nfv based networks the role of network coding and redundant computing"):
  with members:
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "gradient coding from cyclic mds codes and expander graphs"
    - "coded computation against processing delays for virtualized cloud based channel decoding"
    - "coded fourier transform"
    - "a fundamental tradeoff between computation and communication in distributed computing"
    - "a scalable framework for wireless distributed computing"
    - "specifying and placing chains of virtual network functions"

Connected through hyperedge HE-2 (induced by source paper "coded computation against processing delays for virtualized cloud based channel decoding"):
  with members:
    - "learning a code machine learning for approximate non linear coded computation"
    - "speeding up distributed machine learning using codes"
    - "rateless codes for near perfect load balancing in distributed matrix vector multiplication"
    - "coded iterative computing using substitute decoding"
    - "coded computation over heterogeneous clusters"
    - "on the trade off between computational load and reliability for network function virtualization"
    - "polynomial codes an optimal design for high dimensional coded matrix multiplication"
    - "block diagonal coding for distributed computing with straggling servers"

Connected through hyperedge HE-3 (induced by source paper "coded computation against straggling decoders for network function virtualization"):
  with members:
    - "speeding up distributed machine learning using codes"
    - "block diagonal coding for distributed computing with straggling servers"
    - "a fundamental tradeoff between computation and communication in distributed computing"
    - "network function virtualization state of the art and research challenges"

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.IT(Information Theory)