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 "system of systems modeling analysis and optimization of hybrid vehicular traffic"):
  Abstract: While the development of fully autonomous vehicles is one of the major research fields in the Intelligent Transportation Systems (ITSs) domain, the upcoming long-term transition period – the hybrid vehicular traffic – is often neglected. However, within the next decades, automotive systems with heterogeneous autonomy levels will share the same road network, resulting in new problems for traffic management systems and communication network infrastructure providers. In this paper, we identify key challenges of the upcoming hybrid traffic scenario and present a system-of-systems model, which brings together approaches and methods from traffic modeling, data science, and communication engineering in order to allow data-driven traffic flow optimization. The proposed model consists of data acquisition, data transfer, data analysis, and data exploitation and exploits real world sensor data as well as simulative optimization methods. Based on the results of multiple case studies, which focus on individual challenges (e.g., resource-efficient data transfer and dynamic routing of vehicles), we point out approaches for using the existing infrastructure with a higher grade of efficiency.

Includes members:
  Member "machine learning based context predictive car to cloud communication using multi layer connectivity maps for upcoming 5g networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a reinforcement learning approach for efficient opportunistic vehicle to cloud data transfer")
  Member "machine learning based uplink transmission power prediction for lte and upcoming 5g networks using passive downlink indicators":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "limits lightweight machine learning for iot systems with resource limitations")
  Member "lightweight joint simulation of vehicular mobility and communication with limosim":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "lightweight simulation of hybrid aerial and ground based vehicular communication networks")
  Member "connected vehicular transportation data analytics and traffic dependent networking":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "data driven network simulation for performance analysis of anticipatory vehicular communication systems")
  Member "b a t mobile leveraging mobility control knowledge for efficient routing in mobile robotic networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lightweight simulation of hybrid aerial and ground based vehicular communication networks")
  Member "a survey of anticipatory mobile networking context based classification prediction methodologies and optimization techniques":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "limits lightweight machine learning for iot systems with resource limitations")

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)