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 "exploiting moving intelligence delay optimized computation offloading in vehicular fog networks"):
  Abstract: Future vehicles will have rich computing resources to support autonomous driving and be connected by wireless technologies. Vehicular fog networks (VeFN) have thus emerged to enable computing resource sharing via computation task offloading, providing wide range of fog applications. However, the high mobility of vehicles makes it hard to guarantee the delay that accounts for both communication and computation throughout the whole task offloading procedure. In this article, we first review the state-of-the-art of task offloading in VeFN, and argue that mobility is not only an obstacle for timely computing in VeFN, but can also benefit the delay performance. We then identify machine learning and coded computing as key enabling technologies to address and exploit mobility in VeFN. Case studies are provided to illustrate how to adapt learning algorithms to fit for the dynamic environment in VeFN, and how to exploit the mobility with opportunistic computation offloading and task replication.

Includes members:
  Member "learning based task offloading for vehicular cloud computing systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed task replication for vehicular edge computing performance analysis and learning based algorithm")
  Member "coding for distributed fog computing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  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 "towards low latency and ultra reliable vehicle to vehicle communication":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimized age of information tail for ultra reliable low latency communications in vehicular networks")
  Member "task replication for deadline constrained vehicular cloud computing optimal policy performance analysis and implications on road traffic":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "age of information optimized mac in v2x sidelink via piggyback based collaboration")
  Member "effect of user mobility on the performance of device to device networks with distributed caching":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mobility aware content preference learning in decentralized caching networks")
  Member "effect of retransmissions on optimal caching in cache enabled small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "stochastic design and analysis of wireless cloud caching 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)