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 "joint communication computation caching and control in big data multi access edge computing"):
  Abstract: The concept of multi-access edge computing (MEC) has been recently introduced to supplement cloud computing by deploying MEC servers to the network edge so as to reduce the network delay and alleviate the load on cloud data centers. However, compared to a resourceful cloud, an MEC server has limited resources. When each MEC server operates independently, it cannot handle all of the computational and big data demands stemming from the users devices. Consequently, the MEC server cannot provide significant gains in overhead reduction due to data exchange between users devices and remote cloud. Therefore, joint computing, caching, communication, and control (4C) at the edge with MEC server collaboration is strongly needed for big data applications. In order to address these challenges, in this paper, the problem of joint 4C in big data MEC is formulated as an optimization problem whose goal is to maximize the bandwidth saving while minimizing delay, subject to the local computation capability of user devices, computation deadline, and MEC resource constraints. However, the formulated problem is shown to be non-convex. To make this problem convex, a proximal upper bound problem of the original formulated problem that guarantees descent to the original problem is proposed. To solve the proximal upper bound problem, a block successive upper bound minimization (BSUM) method is applied. Simulation results show that the proposed approach increases bandwidth-saving and minimizes delay while satisfying the computation deadlines.

Includes members:
  Member "deep learning for reliable mobile edge analytics in intelligent transportation systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal time allocation in vanets advertising a price based approach using stackelberg game")
  Member "proactive edge computing in latency constrained fog networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "wireless edge computing with latency and reliability guarantees")
  Member "a survey on mobile edge computing the communication perspective":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "an online secretary framework for fog network formation with minimal latency":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "all one needs to know about fog computing and related edge computing paradigms a complete survey")
  Member "stochastic joint radio and computational resource management for multi user mobile edge computing systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi agent meta reinforcement learning for self powered and sustainable edge computing systems")
  Member "energy efficient resource allocation for cache assisted mobile edge computing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "edge computing enabled smart cities a comprehensive survey")
  Member "network slicing for service oriented networks under resource constraints":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coexistence mechanism between embb and urllc in 5g wireless networks")
  Member "artificial neural networks based machine learning for wireless networks a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "fog computing systems state of the art research issues and future trends")

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)