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: "beaconless georouting under the spotlight practical link models and application scenarios"
  Abstract: Beaconless georouting has emerged as a viable packetforwarding technique in distributed wireless networks, particularly for applications requiring portability and scalability. In this paper, we focus on fine-tuning and developing the analytical tools associated with the study of beaconless georouting protocols. For instance, they have been traditionally analyzed and simulated from the perspective of a single hop only. However, end-to-end performance analysis is instrumental when considering practical application scenarios. Furthermore, beaconless georouting protocols have been studied in literature assuming equal communication ranges for the data and control packets. In reality, this is not true since the communication range is actually a function of the packet length (among other factors). Control packets are typically much shorter than data packets. As a consequence, a substantial discrepancy exists in practice between their respective communication ranges, causing many data packet drops. Accordingly, we introduce two simple strategies for bridging the gap between the control and data packet communication ranges. Our primary objective in this paper is to construct a realistic analysis describing the end-to-end performance of beaconless georouting protocols. Two flagship protocols are selected in this paper for further investigation. For a better perspective, the two protocols are actually compared to a hypothetical limit case, one which offers optimal energy and latency performance. Finally, we present four different application scenarios. For each scenario, we highlight the georouting protocol which performs the best and discuss the reasons behind it.

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)