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: "bounds for energy efficient survivable ip over wdm networks with network coding"
  Abstract: In this work, we establish analytic bounds for the energy efficiency of 1+1 survivable IP over WDM networks using network coding. The analytic bounds are shown to be in close agreement with our previously reported results. They provide verification of the MILP and heuristics proposed previously, in addition to an efficient, compact means to evaluate network results and allow the performance of large networks to be determined easily.

Connected through hyperedge HE-1 (induced by source paper "energy efficient virtual machines placement over cloud fog network architecture"):
  with members:
    - "big data analytics for wireless and wired network design a survey"
    - "patient centric cellular networks optimization using big data analytics"
    - "energy efficient iot virtualization framework with peer to peer networking and processing"
    - "optimized energy aware 5g network function virtualization"

Connected through hyperedge HE-2 (induced by source paper "a survey of big data machine learning applications optimization in cloud data centers and networks"):
  with members:
    - "fog assisted caching employing solar renewable energy for delivering video on demand service"
    - "energy efficient and resilient infrastructure for fog computing health monitoring applications"
    - "virtual machines embedding for cloud pon awgr and server based data centres"
    - "a survey on geographically distributed big data processing using mapreduce"
    - "disaggregation for improved efficiency in fog computing era"
    - "experimental evaluation of server centric passive optical network based data centre architecture"
    - "energy efficient distributed processing in vehicular cloud architecture"
    - "energy efficient software matching in vehicular fog"

Connected through hyperedge HE-3 (induced by source paper "energy efficient routing and network coding in core networks"):
  with members:
    - "big data analytics for wireless and wired network design a survey"
    - "patient centric cellular networks optimization using big data analytics"
    - "energy efficient iot virtualization framework with peer to peer networking and processing"
    - "optimized energy aware 5g network function virtualization"
    - "optimization based linear network coding for general connections of continuous flows"
    - "overlay protection against link failures using network coding"
    - "network protection codes against link failures using network coding"
    - "genetic representations for evolutionary minimization of network coding resources"

Connected through hyperedge HE-4 (induced by source paper "resilient service embedding in iot networks"):
  with members:
    - "service embedding in iot networks"
    - "big data analytics for wireless and wired network design a survey"
    - "patient centric cellular networks optimization using big data analytics"
    - "energy efficient iot virtualization framework with peer to peer networking and processing"
    - "energy efficiency of server centric pon data center architecture for fog computing"
    - "optimized energy aware 5g network function virtualization"

Connected through hyperedge HE-5 (induced by source paper "energy efficient and resilient infrastructure for fog computing health monitoring applications"):
  with members:
    - "big data analytics for wireless and wired network design a survey"
    - "patient centric cellular networks optimization using big data analytics"
    - "energy efficiency of fog computing health monitoring applications"
    - "optimized energy aware 5g network function virtualization"
    - "server placement with shared backups for disaster resilient clouds"

Connected through hyperedge HE-6 (induced by source paper "virtual machines embedding for cloud pon awgr and server based data centres"):
  with members:
    - "big data analytics for wireless and wired network design a survey"
    - "patient centric cellular networks optimization using big data analytics"
    - "impact of link failures on the performance of mapreduce in data center networks"
    - "energy efficiency of server centric pon data center architecture for fog computing"
    - "optimized energy aware 5g network function virtualization"

Connected through hyperedge HE-7 (induced by source paper "experimental evaluation of server centric passive optical network based data centre architecture"):
  with members:
    - "big data analytics for wireless and wired network design a survey"
    - "patient centric cellular networks optimization using big data analytics"
    - "experimental evaluation of passive optical network based data centre architecture"
    - "energy efficiency of server centric pon data center architecture for fog computing"
    - "optimized energy aware 5g network function virtualization"

Connected through hyperedge HE-8 (induced by source paper "impact of distributed processing on power consumption for iot based surveillance applications"):
  with members:
    - "big data analytics for wireless and wired network design a survey"
    - "energy efficient service distribution in internet of things"
    - "patient centric cellular networks optimization using big data analytics"
    - "the internet of things fog and cloud continuum integration and challenges"
    - "optimized energy aware 5g network function virtualization"

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)