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 "resource management and admission control for tactile internet in next generation of ran"):
  Abstract: In this paper, a new queuing model for the Tactile Internet (TI) is proposed for the cloud radio access network (C-RAN) architecture of the next generation wireless networks, e.g., 5G, assisted via orthogonal frequency division multiple access (OFDMA) technology. This model includes both the radio remote head (RRH) and baseband processing unit (BBU) queuing delays and reliability for each end to end (E2E) connection between each pair of tactile users. For this setup, with the aim to minimize the transmit power of users subject to guaranteeing tolerable delay of users, and fronthaul and access limitations, we formulate a resource allocation problem. Since the proposed optimization problem is highly non-convex, to solve it in an efficient manner, we utilize diverse transformation techniques such as successive convex approximation (SCA) and difference of two convex functions (DC). In addition, we propose an admission control (AC) algorithm to make problem feasible. In our proposed system model, we dynamically adjust the fronthaul and access links to minimize the transmit power. Simulation results reveal that by dynamic adjustment of the access and fronthaul delays, transmit power can be saved compared to the case of fixed approach per each transmission session. Moreover, the number of rejected users in the network is significantly reduced and more users are accepted.

Includes members:
  Member "improving network availability of ultra reliable and low latency communications with multi connectivity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cross layer design for mission critical iot in mobile edge computing systems")
  Member "joint uplink and downlink resource configuration for ultra reliable and low latency communications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "random access based reliable uplink communication and power transfer using dynamic power splitting")
  Member "network slicing based 5g and future mobile networks mobility resource management and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")
  Member "realizing the tactile internet haptic communications over next generation 5g cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analyzing the tradeoffs in using millimeter wave directional links for high data rate tactile internet applications")
  Member "joint millimeter wave fronthaul and ofdma resource allocation in ultra dense cran":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint beamforming and power splitting design for c ran with multicast fronthaul")
  Member "uplink transmission design with massive machine type devices in tactile internet":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards tactile internet in beyond 5g era recent advances current issues and future directions")
  Member "fronthauling for 5g lte u ultra dense cloud small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint fronthaul multicast and cooperative beamforming for cache enabled cloud based small cell networks an mds codes aided approach")
  Member "joint user association and resource allocation in virtualized wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mode selection and resource allocation in sliced fog radio access networks a reinforcement learning approach")

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)