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: "fundamentals of large sensor networks connectivity capacity clocks and computation"
  Abstract: Sensor networks potentially feature large numbers of nodes. The nodes can monitor and sense their environment over time, communicate with each other over a wireless network, and process information that they exchange with each other. They differ from data networks in that the network as a whole may be designed for a specific application. We study the theoretical foundations of such large-scale sensor networks. We address four fundamental organizational and operational issues related to large sensor networks: connectivity, capacity, clocks, and function computation. To begin with, a sensor network must be connected so that information can indeed be exchanged between nodes. The connectivity graph of an ad hoc network is modeled as a random graph and the critical range for asymptotic connectivity is determined, as well as the critical number of neighbors that a node needs to connect to. Next, given connectivity, we address the issue of how much data can be transported over the sensor network. We present fundamental bounds on capacity under several models, as well as architectural implications for how wireless communication should be organized. Temporal information is important both for the applications of sensor networks as well as their operation. We present fundamental bounds on the synchronizability of clocks in networks, and also present and analyze algorithms for clock synchronization. Finally, we turn to the issue of gathering relevant information, which sensor networks are designed to do. One needs to study optimal strategies for in-network aggregation of data, in order to reliably compute a composite function of sensor measurements, as well as the complexity of doing so. We address the issue of how such computation can be performed efficiently in a sensor network and the algorithms for doing so, for some classes of functions.

Connected through hyperedge HE-1 (induced by source paper "cooperative network synchronization asymptotic analysis"):
  with members:
    - "on the outage probability of localization in randomly deployed wireless networks"
    - "a scalable algorithm for tracking an unknown number of targets using multiple sensors"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "cooperative simultaneous localization and synchronization in mobile agent networks"
    - "cooperative joint localization and clock synchronization based on gaussian message passing in asynchronous wireless networks"
    - "performance limits and geometric properties of array localization"
    - "distributed clock skew and offset estimation in wireless sensor networks asynchronous algorithm and convergence analysis"
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"

Connected through hyperedge HE-2 (induced by source paper "a software defined architecture for control of iot cyberphysical systems"):
  with members:
    - "dynamic watermarking active defense of networked cyber physical systems"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-3 (induced by source paper "distributed algorithms for computation of centrality measures in complex networks"):
  with members:
    - "stability and continuity of centrality measures in weighted graphs"
    - "ergodic randomized algorithms and dynamics over networks"
    - "convergence of distributed randomized pagerank algorithms"
    - "axioms for centrality"
    - "explicit convergence rate of a distributed alternating direction method of multipliers"
    - "distributed randomized algorithms for the pagerank computation"

Connected through hyperedge HE-4 (induced by source paper "scalable and passive wireless network clock synchronization in los environments"):
  with members:
    - "joint ranging and clock parameter estimation by wireless round trip time measurements"
    - "experimental demonstration of nanosecond accuracy wireless network synchronization"
    - "cooperative synchronization in wireless networks"
    - "an experimental investigation of simo mimo interference alignment ia and coordinated multi point comp"
    - "femtocell networks a survey"

Connected through hyperedge HE-5 (induced by source paper "timing and carrier synchronization in wireless communication systems a survey and classification of research in the last 5 years"):
  with members:
    - "performance analysis of arbitrarily shaped underlay cognitive networks effects of secondary user activity protocols"
    - "directional cell discovery in millimeter wave cellular networks"
    - "training based synchronization and channel estimation in af two way relaying networks"
    - "improving bandwidth efficiency in e band communication systems"
    - "wireless networks with rf energy harvesting a contemporary survey"
    - "what will 5g be"
    - "channel phase noise and frequency offset in ofdm systems joint estimation data detection and hybrid cramer rao lower bound"
    - "time and frequency synchronization for multicarrier transmission on hexagonal time frequency lattice"

Connected through hyperedge HE-6 (induced by source paper "sampling rate distortion"):
  with members:
    - "distortion rate function of sub nyquist sampled gaussian sources"
    - "near optimal sensor placement for linear inverse problems"
    - "dass distributed adaptive sparse sensing"
    - "intersensor collaboration in distributed quantization networks"
    - "lossy computing of correlated sources with fractional sampling"
    - "sampling high dimensional bandlimited fields on low dimensional manifolds"
    - "optimal phase transitions in compressed sensing"
    - "the sampling rate distortion tradeoff for sparsity pattern recovery in compressed sensing"

Connected through hyperedge HE-7 (induced by source paper "rigid body localization using sensor networks position and orientation estimation"):
  with members:
    - "sparsity exploiting anchor placement for localization in sensor networks"
    - "position and orientation estimation of a rigid body rigid body localization"

Connected through hyperedge HE-8 (induced by source paper "target assignment in robotic networks distance optimality guarantees and hierarchical strategies"):
  with members:
    - "asymptotically optimal algorithms for one to one pickup and delivery problems with applications to transportation systems"
    - "distance optimal formation control on graphs with a tight convergence time guarantee"

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)