human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "dynamic mobility aware interference avoidance for aerial base stations in cognitive radio networks"
  Abstract: Aerial base station (ABS) is a promising solution for public safety as it can be deployed in coexistence with cellular networks to form a temporary communication network. However, the interference from the primary cellular network may severely degrade the performance of an ABS network. With this consideration, an adaptive dynamic interference avoidance scheme is proposed in this work for ABSs coexisting with a primary network. In the proposed scheme, the mobile ABSs can reconfigure their locations to mitigate the interference from the primary network, so as to better relay the data from the designated source(s) to destination(s). To this end, the single/multi-commodity maximum flow problems are formulated and the weighted Cheeger constant is adopted as a criterion to improve the maximum flow of the ABS network. In addition, a distributed algorithm is proposed to compute the optimal ABS moving directions. Moreover, the trade-off between the maximum flow and the shortest path trajectories is investigated and an energy-efficient approach is developed as well. Simulation results show that the proposed approach is effective in improving the maximum network flow and the energy-efficient approach can save up to 39% of the energy for the ABSs with marginal degradation in the maximum network flow.

Connected through hyperedge HE-1 (induced by source paper "drones in distress a game theoretic countermeasure for protecting uavs against gps spoofing"):
  with members:
    - "a game of drones cyber physical security of time critical uav applications with cumulative prospect theory perceptions and valuations"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "machine learning for wireless connectivity and security of cellular connected uavs"
    - "robust deep reinforcement learning for security and safety in autonomous vehicle systems"
    - "cyber physical security and safety of autonomous connected vehicles optimal control meets multi armed bandit learning"
    - "mobile unmanned aerial vehicles uavs for energy efficient internet of things communications"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"
    - "single controller stochastic games for optimized moving target defense"

Connected through hyperedge HE-2 (induced by source paper "interference avoidance position planning in dual hop and multi hop uav relay networks"):
  with members:
    - "local map assisted positioning for flying wireless relays"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "optimal 1d trajectory design for uav enabled multiuser wireless power transfer"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "network formation in the sky unmanned aerial vehicles for multi hop wireless backhauling"
    - "energy efficient uav communication with trajectory optimization"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "mobile internet of things can uavs provide an energy efficient mobile architecture"

Connected through hyperedge HE-3 (induced by source paper "optimal time allocation in vanets advertising a price based approach using stackelberg game"):
  with members:
    - "robust deep reinforcement learning for security and safety in autonomous vehicle systems"
    - "deep learning for reliable mobile edge analytics in intelligent transportation systems"

Connected through hyperedge HE-4 (induced by source paper "interference avoidance in uav assisted networks joint 3d trajectory design and power allocation"):
  with members:
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"

Connected through hyperedge HE-5 (induced by source paper "human in the loop wireless communications machine learning and brain aware resource management"):
  with members:
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "robust deep reinforcement learning for security and safety in autonomous vehicle systems"
    - "virtual reality over wireless networks quality of service model and learning based resource management"
    - "artificial neural networks based machine learning for wireless networks a tutorial"
    - "context aware small cell networks how social metrics improve wireless resource allocation"
    - "prospect pricing in cognitive radio networks"
    - "context aware computing for the internet of things a survey"

Question: Please tell me which class the center node 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)