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: "lschc layered static context header compression for lpwans"
  Abstract: Supporting IPv6/UDP/CoAP protocols over Low Power Wide Area Networks (LPWANs) can bring open networking, interconnection, and cooperation to this new type of Internet of Things networks. However, accommodating these protocols over these very low bandwidth networks requires efficient header compression schemes to meet the limited frame size of these networks, where only one or two octets are available to transmit all headers. Recently, the Internet Engineering Task Force (IETF) LPWAN working group drafted the Static Context Header Compression (SCHC), a new header compression scheme for LPWANs, which can provide a good compression factor without complex synchronization. In this paper, we present an implementation and evaluation of SCHC. We compare SCHC with IPHC, which also targets constrained networks. Additionally, we propose an enhancement of SCHC, Layered SCHC (LSCHC). LSCHC is a layered context that reduces memory consumption and processing complexity, and adds flexibility when compressing packets. Finally, we perform calculations to show the impact of SCHC/LSCHC on an example LPWAN technology, e.g. LoRaWAN, from the point of view of transmission time and reliability.

Connected through hyperedge HE-1 (induced by source paper "fair adaptive data rate allocation and power control in lorawan"):
  with members:
    - "on lorawan scalability empirical evaluation of susceptibility to inter network interference"
    - "low power wide area network analysis can lora scale"
    - "low power wide area networks an overview"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

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)