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: "integrating small satellite communication in an autonomous vehicle network a case for oceanography"
  Abstract: Abstract   Small satellites and autonomous vehicles have greatly evolved in the last few decades. Hundreds of small satellites have been launched with increasing functionalities, in the last few years. Likewise, numerous autonomous vehicles have been built, with decreasing costs and form-factor payloads. Here we focus on combining these two multifaceted assets in an incremental way, with an ultimate goal of alleviating the logistical expenses in remote oceanographic operations. The first goal is to create a highly reliable and constantly available communication link for a network of autonomous vehicles, taking advantage of the small satellite lower cost, with respect to conventional spacecraft, and its higher flexibility. We have developed a test platform as a proving ground for this network, by integrating a satellite software defined radio on an unmanned air vehicle, creating a system of systems, and several tests have been run successfully, over land. As soon as the satellite is fully operational, we will start to move towards a cooperative network of autonomous vehicles and small satellites, with application in maritime operations, both in-situ and remote sensing.

Connected through hyperedge HE-1 (induced by source paper "potential data link candidates for civilian unmanned aircraft systems a survey"):
  with members:
    - "analysis of aeromacs data link for unmanned aircraft vehicles"
    - "understanding uav cellular communications from existing networks to massive mimo"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "real time optimal resource allocation for embedded uav communication systems"
    - "robust resource allocation for uav systems with uav jittering and user location uncertainty"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "spatial configuration of agile wireless networks with drone bss and user in the loop"
    - "joint trajectory and communication design for uav enabled multiple access"

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)