human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "tackling contention through cooperation a distributed federation in lorawan space"):
  Abstract: Low-Power Wide Area Networks (LPWAN) play a key role in the IoT marketplace wherein LoRaWAN is considered a leading solution. Despite the traction of LoRaWAN, research shows that the current contention management mechanisms of LoRaWAN do not scale. This paper tackles contention on LoRaWAN by introducing FLIP, a fully distributed and open architecture for LoRaWAN that fundamentally rethinks how LoRa gateways should be managed and coordinated. FLIP transforms LoRa gateways into a federated network that provides inherent support for roaming while tackling contention using consensus-driven load balancing. FLIP offers identical security guarantees to LoRaWAN, is compatible with existing gateway hardware and requires no updates to end-device hardware or firmware. These features ensure the practicality of FLIP and provide a path to its adoption. We evaluate the performance of FLIP in a large-scale real-world deployment and demonstrate that FLIP delivers scalable roaming and improved contention management in comparison to LoRaWAN. FLIP achieves these benefits within the resource constraints of conventional LoRa gateways and requires no server hardware.

Includes members:
  Member "on lorawan scalability empirical evaluation of susceptibility to inter network interference":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capture aware sequential waterfilling for lorawan adaptive data rate")
  Member "does bidirectional traffic do more harm than good in lorawan based lpwa networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a thorough study of lorawan performance under different parameter settings")
  Member "low power wide area network analysis can lora scale":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance analysis of single cell adaptive data rate enabled lorawan")
  Member "low power wide area networks an overview":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "random access based reliable uplink communication and power transfer using dynamic power splitting")
  Member "mitigating inter network interference in lora networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "performance analysis of clustered lora networks")

Question: Please tell me which class the source paper 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)