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 "unmanned aerial vehicles in logistics efficiency gains and communication performance of hybrid combinations of ground and aerial vehicles"):
  Abstract: Unmanned Aerial Vehicles (UAVs) have drastically gained popularity in various Intelligent Transportation System (ITS) applications to improve the safety and efficiency of transportation systems. In this context, the combination of ground vehicles, such as delivery trucks, with drones to assist in the last mile pick-up and delivery of the parcels has been recently proposed. While aerial vehicles promise increased efficiency based on flexible routes and parallelized operation, highly reliable wireless communication is also required for the control and coordination of potentially many drones acting in a self-organized way. In this paper, we analyze the improvements procured by drone usage in parcel delivery compared to traditional delivery and propose a simulation framework to further quantify the efficiency gains of the parcel delivery logistics and to analyze the performance of different wireless communications options. To this end, we consider a heterogeneous vehicle routing problem with various constraints. We consider two approaches regarding the dispatching and recovery of drones and evaluate their benefits as opposed to parcel delivery with a classic truck only. Furthermore, we compare two networking technologies for enabling coordination of the self-organizing teams of drones with a realistically modeled environment: one approach relying on base station oriented Long Term Evolution (LTE) vs. a more decentralized Cellular Vehicle-to-Everything (C-V2X) solution. The results show time savings of nearly 40% can be achieved through drone usage and that the negative impact of urban shadowing on network communications in the base station oriented LTE approach can be compensated by leveraging decentralized C-V2X communications

Includes members:
  Member "lightweight simulation of hybrid aerial and ground based vehicular communication networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "performance analysis of c v2x mode 4 communication introducing an open source c v2x simulator")
  Member "system of systems modeling analysis and optimization of hybrid vehicular traffic":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "limits lightweight machine learning for iot systems with resource limitations")
  Member "boosting vehicle to cloud communication by machine learning enabled context prediction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "limits lightweight machine learning for iot systems with resource limitations")
  Member "uav communications for 5g and beyond recent advances and future trends":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "physical layer security for noma transmission in mmwave drone networks")
  Member "performance analysis of c v2x mode 4 communication introducing an open source c v2x simulator":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lightweight simulation of hybrid aerial and ground based vehicular communication networks")
  Member "the sky is not the limit lte for unmanned aerial vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "performance analysis of mobile cellular connected drones under practical antenna configurations")
  Member "lightweight joint simulation of vehicular mobility and communication with limosim":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "lightweight simulation of hybrid aerial and ground based vehicular communication networks")
  Member "b a t mobile leveraging mobility control knowledge for efficient routing in mobile robotic networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lightweight simulation of hybrid aerial and ground based vehicular communication 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)