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: "average peak age of information minimization in uav assisted iot networks"
  Abstract: Motivated by the need to ensure timely delivery of information (e.g., status updates) in the Internet-of-Things (IoT) paradigm, this paper investigates the role of an unmanned aerial vehicle (UAV) as a mobile relay to minimize the average peak age-of-information for a source–destination pair. For this setup, we formulate an optimization problem to jointly optimize the UAV's flight trajectory as well as energy and service time allocations for packet transmissions. In order to solve this non-convex problem, we propose an efficient iterative algorithm and establish its convergence analytically. Closed-form solutions for some sub-problems are also provided. One of the sub-problems we solve in this procedure is to jointly optimize the energy and service time allocations for a given trajectory of the UAV. This problem is of interest on its own right because in some cases we may not be able to alter the UAV's trajectory based on the locations of the IoT devices (especially when its primary mission is something else). Our numerical results quantify the gains that can be achieved by additionally optimizing the UAV's trajectory.

Connected through hyperedge HE-1 (induced by source paper "who should google scholar update more often"):
  with members:
    - "optimal selective encoding for timely updates"
    - "trading off computation with transmission in status update systems"
    - "a reinforcement learning framework for optimizing age of information in rf powered communication systems"
    - "age of information aware cache updating with file and age dependent update durations"
    - "reducing age of information for computation intensive messages via packet replacement"
    - "timely distributed computation with stragglers"
    - "age of information in multicast networks with multiple update streams"
    - "age of information for updates with distortion constant and age dependent distortion constraints"

Connected through hyperedge HE-2 (induced by source paper "optimized age of information tail for ultra reliable low latency communications in vehicular networks"):
  with members:
    - "a general formula for the stationary distribution of the age of information and its application to single server queues"
    - "optimal control of status updates in a multiple access channel with stability constraints"
    - "saddlepoint approximations for rayleigh block fading channels"
    - "optimal status updating with a finite battery energy harvesting source"
    - "statistical guarantee optimization for aoi in single hop and two hop systems with periodic arrivals"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "dynamic task offloading and resource allocation for ultra reliable low latency edge computing"
    - "ultra reliable low latency vehicular networks taming the age of information tail"

Connected through hyperedge HE-3 (induced by source paper "age of information for multicast transmission with fixed and random deadlines in iot systems"):
  with members:
    - "age of information for computation intensive messages in mobile edge computing"
    - "economics of age of information management under network externalities"
    - "minimizing the age of information in wireless networks with stochastic arrivals"
    - "broadcast age of information in csma ca based wireless networks"
    - "adaptive coding for information freshness in a two user broadcast erasure channel"
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "age minimal online policies for energy harvesting sensors with random battery recharges"
    - "reinforcement learning based scheduling algorithm for optimizing age of information in ultra reliable low latency networks"

Connected through hyperedge HE-4 (induced by source paper "deep reinforcement learning for fresh data collection in uav assisted iot networks"):
  with members:
    - "age optimal trajectory planning for uav assisted data collection"
    - "timely status update in massive iot systems decentralized scheduling for wireless uplinks"
    - "energy minimization for wireless communication with rotary wing uav"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "energy efficient uav communication with trajectory optimization"
    - "update or wait how to keep your data fresh"

Connected through hyperedge HE-5 (induced by source paper "on the 3 d placement of airborne base stations using tethered uavs"):
  with members:
    - "capacity and coverage enhancement using long endurance tethered airborne base stations"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "cellular connectivity for uavs network modeling performance analysis and design guidelines"
    - "cellular uav to uav communications"
    - "understanding uav cellular communications from existing networks to massive mimo"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "post disaster 4g 5g network rehabilitation using drones solving battery and backhaul issues"
    - "backhaul aware placement of a uav bs with bandwidth allocation for user centric operation and profit maximization"

Connected through hyperedge HE-6 (induced by source paper "minimum age of information in the internet of things with non uniform status packet sizes"):
  with members:
    - "age optimal transmission of rateless codes in an erasure channel"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "a reinforcement learning approach to age of information in multi user networks"
    - "can decentralized status update achieve universally near optimal age of information in wireless multiaccess channels"
    - "sampling for data freshness optimization non linear age functions"
    - "controlling packet drops to improve freshness of information"
    - "joint status sampling and updating for minimizing age of information in the internet of things"
    - "optimizing information freshness in wireless networks under general interference constraints"

Connected through hyperedge HE-7 (induced by source paper "hybrid offline online design for uav enabled data harvesting in probabilistic los channel"):
  with members:
    - "efficient local map search algorithms for the placement of flying relays"
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "deep reinforcement learning for minimizing age of information in uav assisted networks"
    - "3d trajectory optimization in rician fading for uav enabled data harvesting"
    - "path design for cellular connected uav with reinforcement learning"
    - "age optimal trajectory planning for uav assisted data collection"
    - "local map assisted positioning for flying wireless relays"
    - "learning to communicate in uav aided wireless networks map based approaches"

Connected through hyperedge HE-8 (induced by source paper "a reinforcement learning framework for optimizing age of information in rf powered communication systems"):
  with members:
    - "timely updates in energy harvesting two hop networks offline and online policies"
    - "age optimal trajectory planning for uav assisted data collection"
    - "ultra reliable low latency vehicular networks taming the age of information tail"
    - "sending information through status updates"
    - "optimal status update for age of information minimization with an energy harvesting source"
    - "timely updates over an erasure channel"
    - "age and value of information non linear age case"
    - "update or wait how to keep your data fresh"

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)