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: "panda neighbor discovery on a power harvesting budget"
  Abstract: Object tracking applications are gaining popularity and will soon utilize Energy Harvesting (EH) low-power nodes that will consume power mostly for Neighbor Discovery (ND) (i.e., identifying nodes within communication range). Although ND protocols were developed for sensor networks, the challenges posed by emerging EH low-power transceivers were not addressed. Therefore, we design an ND protocol tailored for the characteristics of a representative EH prototype: the TI eZ430-RF2500-SEH. We present a generalized model of ND accounting for unique prototype characteristics (i.e., energy costs for transmission/reception, and transceiver state switching times/costs). Then, we present the Power Aware Neighbor Discovery Asynchronously (Panda) protocol in which nodes transition between the sleep, receive, and transmit states. We analyze \name and select its parameters to maximize the ND rate subject to a homogeneous power budget. We also present Panda-D, designed for non-homogeneous EH nodes. We perform extensive testbed evaluations using the prototypes and study various design tradeoffs. We demonstrate a small difference (less then 2%) between experimental and analytical results, thereby confirming the modeling assumptions. Moreover, we show that Panda improves the ND rate by up to 3x compared to related protocols. Finally, we show that Panda-D operates well under non-homogeneous power harvesting.

Connected through hyperedge HE-1 (induced by source paper "on optimal neighbor discovery"):
  with members:
    - "neighbor discovery latency in ble like protocols"
    - "talk more listen less energy efficient neighbor discovery in wireless sensor networks"
    - "maximizing broadcast throughput under ultra low power constraints"
    - "slotless protocols for fast and energy efficient neighbor discovery"
    - "on heterogeneous neighbor discovery in wireless sensor networks"
    - "near optimal radio use for wireless network synchronization"
    - "deterministic and energy optimal wireless synchronization"

Connected through hyperedge HE-2 (induced by source paper "neighbor discovery latency in ble like protocols"):
  with members:
    - "maximizing broadcast throughput under ultra low power constraints"
    - "slotless protocols for fast and energy efficient neighbor discovery"
    - "on heterogeneous neighbor discovery in wireless sensor networks"
    - "precise energy modeling for the bluetooth low energy protocol"

Connected through hyperedge HE-3 (induced by source paper "maximizing broadcast throughput under ultra low power constraints"):
  with members:
    - "robust neighbor discovery in multi hop multi channel heterogeneous wireless networks"
    - "energy harvesting wireless communications a review of recent advances"
    - "on heterogeneous neighbor discovery in wireless sensor networks"
    - "queue based random access algorithms fluid limits and stability issues"
    - "movers and shakers kinetic energy harvesting for the internet of things"
    - "on the design of efficient csma algorithms for wireless 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)