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 "energy efficient distributed processing for iot"):
  Abstract: In this paper, the entire IoT-fog-cloud architecture is modelled, the service placement problem is optimized through Mixed Integer Linear Programming (MILP) and the total power consumption is jointly minimized for processing and networking. Four aspects of IoT service placements are examined: 1) non-splittable services, 2) splittable services, 3) inter-service processing overhead for sub-service synchronization and 4) deployment of special-purpose cloud data centers (SP-DCs). The results showed that for a capacitated problem, service splitting introduces power consumption savings of up to 86% compared to 46% with non-splittable services in relation to processing in general-purpose data centers (GP-DCs). Moreover, it is observed that the inter sub-service processing overhead has a great influence on the total number of service splits. However much insignificant the ratio of the processing overhead, the results showed that this is not a trivial matter and hence much attention needs to paid to this area in order to make the best use of the resources that are available in the edge of the network. Moreover, the optimization results showed that, for very high demands, power savings of up to 50% could be achieved with SP-DCs compared to 30% with GP-DCs.

Includes members:
  Member "all one needs to know about fog computing and related edge computing paradigms a complete survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fog computing systems state of the art research issues and future trends")
  Member "service embedding in iot networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "patient centric hetnets powered by machine learning and big data analytics for 6g networks")
  Member "patient centric cellular networks optimization using big data analytics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "patient centric hetnets powered by machine learning and big data analytics for 6g networks")
  Member "energy efficient iot virtualization framework with peer to peer networking and processing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "patient centric hetnets powered by machine learning and big data analytics for 6g networks")
  Member "optimized energy aware 5g network function virtualization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "patient centric hetnets powered by machine learning and big data analytics for 6g networks")
  Member "allocation of heterogeneous resources of an iot device to flexible services":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "energy aware demand selection and allocation for real time iot data trading")

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)