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: "mobile internet of things can uavs provide an energy efficient mobile architecture"
  Abstract: In this paper, the optimal trajectory and deployment of multiple unmanned aerial vehicles (UAVs), used as aerial base stations to collect data from ground Internet of Things (IoT) devices, is investigated. In particular, to enable reliable uplink communications for IoT devices with a minimum energy consumption, a new approach for optimal mobility of the UAVs is proposed. First, given a fixed ground IoT network, the total transmit power of the devices is minimized by properly clustering the IoT devices with each cluster being served by one UAV. Next, to maintain energy-efficient communications in time-varying mobile IoT networks, the optimal trajectories of the UAVs are determined by exploiting the framework of optimal transport theory. Simulation results show that by using the proposed approach, the total transmit power of IoT devices for reliable uplink communications can be reduced by 56% compared to the fixed Voronoi deployment method. Moreover, our results yield the optimal paths that will be used by UAVs to serve the mobile IoT devices with a minimum energy consumption.

Connected through hyperedge HE-1 (induced by source paper "interference avoidance position planning in dual hop and multi hop uav relay networks"):
  with members:
    - "dynamic mobility aware interference avoidance for aerial base stations in cognitive radio networks"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "a qos oriented trajectory optimization in swarming unmanned aerial vehicles communications"):
  with members:
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "uav enabled wireless power transfer trajectory design and energy optimization"

Connected through hyperedge HE-3 (induced by source paper "spatial configuration of agile wireless networks with drone bss and user in the loop"):
  with members:
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "configurations and diagnosis for ultra dense heterogeneous networks from empirical measurements to technical solutions"
    - "dynamic base station repositioning to improve performance of drone small cells"
    - "placement optimization of uav mounted mobile base stations"
    - "user association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations"
    - "optimal transport theory for cell association in uav enabled cellular networks"
    - "energy efficient 3d uav bs placement versus mobile users density and circuit power"
    - "deployment and trajectory optimization for uavs a quantization theory approach"

Connected through hyperedge HE-4 (induced by source paper "common throughput maximization in uav enabled ofdma systems with delay consideration"):
  with members:
    - "capacity characterization of uav enabled two user broadcast channel"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "wireless powered cooperative jamming for secure ofdm system"
    - "dynamic base station repositioning to improve performance of drone small cells"
    - "placement optimization of uav mounted mobile base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "securing uav communications via trajectory optimization"
    - "fundamental green tradeoffs progresses challenges and impacts on 5g networks"

Connected through hyperedge HE-5 (induced by source paper "capacity characterization of uav enabled two user broadcast channel"):
  with members:
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "placement optimization of uav mounted mobile base stations"
    - "dronecells improving 5g spectral efficiency using drone mounted flying base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "securing uav communications via trajectory optimization"
    - "power control in uav supported ultra dense networks communications caching and energy transfer"
    - "joint trajectory and communication design for uav enabled multiple access"
    - "uav enabled wireless power transfer trajectory design and energy optimization"

Connected through hyperedge HE-6 (induced by source paper "a stochastic model for uav networks positioned above demand hotspots in urban environments"):
  with members:
    - "dynamic base station repositioning to improve performance of drone small cells"
    - "backhaul for low altitude uavs in urban environments"
    - "coexistence of terrestrial and aerial users in cellular networks"
    - "energy efficient uav communication with trajectory optimization"
    - "enriched k tier hetnet model to enable the analysis of user centric small cell deployments"
    - "the new frontier in ran heterogeneity multi tier drone cells"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-7 (induced by source paper "overcoming endurance issue uav enabled communications with proactive caching"):
  with members:
    - "uav aided offloading for cellular hotspot"
    - "energy minimization for wireless communication with rotary wing uav"
    - "common throughput maximization in uav enabled ofdma systems with delay consideration"
    - "placement optimization of uav mounted mobile base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "energy efficient data collection in uav enabled wireless sensor network"
    - "joint altitude and beamwidth optimization for uav enabled multiuser communications"
    - "cyclical multiple access in uav aided communications a throughput delay tradeoff"

Connected through hyperedge HE-8 (induced by source paper "multi tier drone architecture for 5g b5g cellular networks challenges trends and prospects"):
  with members:
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "optimal transport theory for power efficient deployment of unmanned aerial vehicles"
    - "analysis of massive mimo enabled downlink wireless backhauling for full duplex small cells"
    - "the new frontier in ran heterogeneity multi tier drone cells"
    - "uav assisted heterogeneous networks for capacity enhancement"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"

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.IT(Information Theory)