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 "a coverage aware resource provisioning method for network slicing"):
  Abstract: Network slicing appears as a key enabler for the future 5G networks. Mobile Network Operators create various slices for Service Providers (SP) to accommodate customized services. As network slices are operated on a common network infrastructure owned by some Infrastructure Provider (InP), sharing the resources across a set of network slices is important for future deployment. Moreover, in many situations, slices have to be deployed over some geographical area: coverage as well as minimum per-user rate constraints have then to be taken into account. #R##N#Usually, the various Service Function Chains (SFCs) belonging to a slice are deployed on a best-effort basis. Nothing ensures that the InP will be able to allocate enough resources to cope with the increasing demands of some SP. This paper takes the InP perspective and proposes a slice resource provisioning approach to cope with multiple slice demands in terms of computing, storage, coverage, and rate constraints. #R##N#The resource requirements of the various Service Function Chains to be deployed within a slice are aggregated within a graph of Slice Resource Demands (SRD). Coverage and rate constraints are also taken into account in the SRD. Infrastructure nodes and links have then to be provisioned so as to satisfy all types of resource demands. This problem leads to a Mixed Integer Linear Programming formulation. A two-step deployment approach is considered, with several variants, depending on whether the constraints of each slide to be deployed are taken into account sequentially or jointly. Once provisioning has been performed, any slice deployment strategy may be considered on the reduced-size infrastructure graph representing the nodes and links on which resources have been provisioned. #R##N#Simulation results demonstrate the effectiveness of the proposed approach compared to a more classical direct slice embedding approach.

Includes members:
  Member "impact of processing resource sharing on the placement of chained virtual network functions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic and application aware provisioning of chained virtual security network functions")
  Member "network service orchestration a survey":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "nfv platform design a survey")
  Member "low complexity distributed radio access network slicing algorithms and experimental results":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "constrained network slicing games achieving service guarantees and network efficiency")
  Member "on the trade off between computational load and reliability for network function virtualization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint reliability aware and cost efficient path allocation and vnf placement using sharing scheme")
  Member "network slicing to enable scalability and flexibility in 5g mobile networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "understanding the computational requirements of virtualized baseband units using a programmable cloud radio access network testbed":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "energy efficiency maximization for c rans discrete monotonic optimization penalty and ell _ 0 approximation methods")
  Member "propagation path loss models for 5g urban micro and macro cellular scenarios":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distributed learning for channel allocation over a shared spectrum")

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)