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: "optimizing data aggregation for uplink machine to machine communication networks"
  Abstract: Machine-to-machine (M2M) communication's severe power limitations challenge the interconnectivity, access management, and reliable communication of data. In densely deployed M2M networks, controlling and aggregating the generated data is critical. We propose an energy efficient data aggregation scheme for a hierarchical M2M network. We develop a coverage probability-based optimal data aggregation scheme for M2M devices to minimize the average total energy expenditure per unit area per unit time or simply the {\em energy density} of an M2M communication network. Our analysis exposes the key tradeoffs between the energy density of the M2M network and the coverage characteristics for successive and parallel transmission schemes that can be either half-duplex or full-duplex. Comparing the rate and energy performances of the transmission models, we observe that successive mode and half-duplex parallel mode have better coverage characteristics compared to full-duplex parallel scheme. Simulation results show that the uplink coverage characteristics dominate the trend of the energy consumption for both successive and parallel schemes.

Connected through hyperedge HE-1 (induced by source paper "hybrid resource scheduling for aggregation in massive machine type communication networks"):
  with members:
    - "finite blocklength communications in smart grids for dynamic spectrum access and locally licensed scenarios"
    - "massive multiple access based on superposition raptor codes for cellular m2m communications"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "aggregation and resource scheduling in machine type communication networks a stochastic geometry approach"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "massive machine type communication with data aggregation and resource scheduling"
    - "maximizing the link throughput between smart meters and aggregators as secondary users under power and outage constraints"
    - "asymptotics and approximation of the sir distribution in general cellular networks"

Connected through hyperedge HE-2 (induced by source paper "energy efficient resource allocation in machine to machine communications with multiple access and energy harvesting for iot"):
  with members:
    - "on user pairing in noma uplink"
    - "distributed user association in energy harvesting small cell networks an exchange economy with uncertainty"
    - "wireless energy harvesting in a cognitive relay network"
    - "power allocation and scheduling for swipt systems with non linear energy harvesting model"
    - "wireless powered communication opportunities and challenges"
    - "downlink power control in two tier cellular networks with energy harvesting small cells as stochastic games"
    - "power and load coupling in cellular networks for energy optimization"
    - "practical non linear energy harvesting model and resource allocation for swipt systems"

Connected through hyperedge HE-3 (induced by source paper "energy efficient massive iot shared spectrum access over uav enabled cellular networks"):
  with members:
    - "cellular connected uav uplink association power control and interference coordination"
    - "performance analysis of uplink cellular iot using different deployments of data aggregators"
    - "aeronautical data aggregation and field estimation in iot networks hovering traveling time dilemma of uavs"
    - "mobile unmanned aerial vehicles uavs for energy efficient internet of things communications"
    - "on the energy distortion tradeoff in the iot"
    - "energy efficient data collection in uav enabled wireless sensor network"
    - "energy efficient uav communication with trajectory optimization"
    - "energy efficient power control a look at 5g wireless technologies"

Connected through hyperedge HE-4 (induced by source paper "wireless data acquisition for edge learning data importance aware retransmission"):
  with members:
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "towards federated learning at scale system design"
    - "label less learning for traffic control in an edge network"
    - "wireless network intelligence at the edge"
    - "federated learning strategies for improving communication efficiency"
    - "broadband analog aggregation for low latency federated edge learning extended version"
    - "federated learning via over the air computation"
    - "fast analog transmission for high mobility wireless data acquisition in edge learning"

Connected through hyperedge HE-5 (induced by source paper "on the benefits of network level cooperation in iot networks with aggregators"):
  with members:
    - "iot u cellular internet of things networks over unlicensed spectrum"
    - "performance analysis of a cooperative wireless network with adaptive relays"
    - "network level cooperation in random access iot networks with aggregators"
    - "performance analysis of uplink cellular iot using different deployments of data aggregators"
    - "on the benefits of network level cooperation in millimeter wave communications"
    - "aggregation and resource scheduling in machine type communication networks a stochastic geometry approach"
    - "wireless network level partial relay cooperation a stable throughput analysis"
    - "massive machine type communication with data aggregation and resource scheduling"

Connected through hyperedge HE-6 (induced by source paper "network level cooperation in random access iot networks with aggregators"):
  with members:
    - "stable throughput and delay analysis of a random access network with queue aware transmission"
    - "aggregation and resource scheduling in machine type communication networks a stochastic geometry approach"
    - "wireless network level partial relay cooperation a stable throughput analysis"
    - "allocation of heterogeneous resources of an iot device to flexible services"
    - "massive machine type communication with data aggregation and resource scheduling"
    - "effect of energy harvesting on stable throughput in cooperative relay systems"
    - "network level performance evaluation of a two relay cooperative random access wireless system"
    - "network level cooperation in energy harvesting wireless networks"

Connected through hyperedge HE-7 (induced by source paper "performance analysis of uplink cellular iot using different deployments of data aggregators"):
  with members:
    - "massive machine type communication with data aggregation and resource scheduling"
    - "heterogeneous cellular networks with flexible cell association a comprehensive downlink sinr analysis"
    - "random deployment of data collectors for serving randomly located sensors"

Connected through hyperedge HE-8 (induced by source paper "aggregation and resource scheduling in machine type communication networks a stochastic geometry approach"):
  with members:
    - "massive multiple access based on superposition raptor codes for cellular m2m communications"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "grant free massive noma outage probability and throughput"
    - "data aggregation and packet bundling of uplink small packets for monitoring applications in lte"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "energy efficient scheduling and grouping for machine type communications over cellular networks"
    - "a delay optimal mac and packet scheduler for heterogeneous m2m uplink"
    - "massive machine type communication with data aggregation and resource scheduling"

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.IT(Information Theory)