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: "an analysis of packet fragmentation impact in lpwan"
  Abstract: Packet fragmentation has mostly been addressed in the literature when referring to splitting data that does not fit a frame. It has received attention in the IoT community after the 6LoWPAN working group of IETF started studying the fragmentation headers to allow IPv6 1280 B MTU to be sent over IEEE 802.15.4 networks supporting a 127 B MTU. In this paper, and following some of the recent directions taken by the IETF LPWAN WG, an analysis of packet fragmentation in LPWANs has been done. We aim to identify the impact of sending the data in smaller fragments considering the restrictions of industrial duty-cycled networks. The analyzed parameters were the energy consumption, throughput, goodput and end to end delay introduced by fragmentation. The results of our analysis show that packet fragmentation can increase the reliability of the communication in duty-cycle restricted networks. This is of especial relevance when densifying the network. We observed relevant impact in energy consumption and extra latency, and identified the need for acknowledgements from the gateway/sink to exploit some of the benefits raised by fragmentation.

Connected through hyperedge HE-1 (induced by source paper "aggressive fragmentation strategy for enhanced network performance in dense lpwans"):
  with members:
    - "does bidirectional traffic do more harm than good in lorawan based lpwa networks"

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)