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 "edge computing aware noma for 5g networks"):
  Abstract: With the fast development of Internet of Things (IoT), the fifth generation (5G) wireless networks need to provide massive connectivity of IoT devices and meet the demand for low latency. To satisfy these requirements, nonorthogonal multiple access (NOMA) has been recognized as a promising solution for 5G networks to significantly improve the network capacity. In parallel with the development of NOMA techniques, mobile edge computing (MEC) is becoming one of the key emerging technologies to reduce the latency and improve the quality of service (QoS) for 5G networks. In order to capture the potential gains of NOMA in the context of MEC, this paper proposes an edge computing aware NOMA technique which can enjoy the benefits of uplink NOMA in reducing MEC users’ uplink energy consumption. To this end, we formulate an NOMA-based optimization framework which minimizes the energy consumption of MEC users via optimizing the user clustering, computing and communication resource allocation, and transmit powers. In particular, similar to frequency resource blocks (RBs), we divide the computing capacity available at the cloudlet to computing RBs. Accordingly, we explore the joint allocation of the frequency and computing RBs to the users that are assigned to different order indices within the NOMA clusters. We also design an efficient heuristic algorithm for user clustering and RBs allocation, and formulate a convex optimization problem for the power control to be solved independently per NOMA cluster. The performance of the proposed NOMA scheme is evaluated via simulations.

Includes members:
  Member "toward hierarchical mobile edge computing an auction based profit maximization approach":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "all one needs to know about fog computing and related edge computing paradigms a complete survey")
  Member "non orthogonal random access nora for 5g networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "signature based non orthogonal multiple access s noma for massive machine type communications in 5g")
  Member "joint subcarrier and cpu time allocation for mobile edge computing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "client selection for federated learning with heterogeneous resources in mobile edge")
  Member "dynamic user clustering and power allocation for uplink and downlink non orthogonal multiple access noma systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "non orthogonal multiple access with orthogonal time frequency space signal transmission")
  Member "uplink non orthogonal multiple access for 5g wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non orthogonal multiple access for 5g and beyond")
  Member "joint optimization of radio resources and code partitioning in mobile cloud computing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "energy efficient joint offloading and wireless resource allocation strategy in multi mec server systems")
  Member "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coexistence mechanism between embb and urllc in 5g 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)