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: "economics of uav aided mobile services deployment"
  Abstract: An Unmanned Aerial Vehicle (UAV) network has emerged as a promising technique to rapidly provide mobile services to a geographical area, where a flying UAV can be deployed close to mobile users to serve as a cell site. However, deployment of UAV-aided mobile services (UMS) faces challenges due to the UAV limitation in wireless coverage and energy storage, which requires both technological and economic schemes in the system level. There are important economic issues regarding the UAV-user interaction for service provision, deployment cost and sustainable deployment of the UAV network. These economic issues are largely overlooked in the literature and this article presents economic solutions for the UMS deployment and operation for providing UMS. As users' locations are their private information and are changing over time, how to ensure users' truthful location reporting is important for determining optimal UAV deployment in serving all the users fairly. However, this is challenging given users' selfishness and a strategic user may misreport his location such that the final UAV placement is closer to himself but further to the other users. We comprehensively present two UAV placement games for best serving all the users while ensuring their truthful location reporting. In addition to addressing the UAV-user interactions via algorithmic game theory, we further study the UAV network sustainability for UMS service provision by minimizing the energy consumption cost during deployment and seeking UAV-UAV cooperation. Though the problems are difficult and shown to be NP-complete, we present tractable deployment solutions for optimizing the bottleneck UAV lifetime and the overall UAV network performance, respectively. Finally, we study the long-term UAV-UAV cooperation in developing various cost-aware patrolling schemes and providing users with dynamic UMS services.

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)