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: "energy aware traffic offloading for green heterogeneous networks"
  Abstract: With small cell base stations (SBSs) densely deployed in addition to conventional macro base stations (MBSs), the heterogeneous cellular network (HCN) architecture can effectively boost network capacity. To support the huge power demand of HCNs, renewable energy harvesting technologies can be leveraged. In this paper, we aim to make efficient use of the harvested energy for on-grid power saving while satisfying the quality of service (QoS) requirement. To this end, energy-aware traffic offloading schemes are proposed, whereby user associations, ON–OFF states of SBSs, and power control are jointly optimized according to the statistical information of energy arrival and traffic load. Specifically, for the single SBS case, the power saving gain achieved by activating the SBS is derived in closed form, based on which the SBS activation condition and optimal traffic offloading amount are obtained. Furthermore, a two-stage energy-aware traffic offloading (TEATO) scheme is proposed for the multiple-SBS case, considering various operating characteristics of SBSs with different power sources. Simulation results demonstrate that the proposed scheme can achieve more than 50% power saving gain for typical daily traffic and solar energy profiles, compared with the conventional traffic offloading schemes.

Connected through hyperedge HE-1 (induced by source paper "network utility maximization based on incentive mechanism for truthful reporting of local information"):
  with members:
    - "applications of economic and pricing models for wireless network security a survey"
    - "joint scheduling and transmission power control in wireless ad hoc networks"
    - "distributed and fair beaconing rate adaptation for congestion control in vehicular networks"
    - "propagation path loss models for 5g urban micro and macro cellular scenarios"
    - "context aware small cell networks how social metrics improve wireless resource allocation"
    - "distributed pricing based user association for downlink heterogeneous cellular networks"
    - "distributed constrained optimization by consensus based primal dual perturbation method"
    - "energy efficiency and spectral efficiency tradeoff in device to device d2d communications"

Connected through hyperedge HE-2 (induced by source paper "wearable affective robot"):
  with members:
    - "joint optimization of computation and communication power in multi user massive mimo systems"
    - "dense small cell networks from noise limited to dense interference limited"
    - "soft defined heterogeneous vehicular network architecture and challenges"
    - "efficient multi user computation offloading for mobile edge cloud computing"

Connected through hyperedge HE-3 (induced by source paper "group server queues"):
  with members:
    - "multi resource energy efficient routing in cloud data centers with networks as a service"
    - "correlating power consumption and network traffic for improving data centers resiliency"
    - "reducing electricity demand charge for data centers with partial execution"
    - "profit aware server allocation for green internet services"
    - "maximizing cloud providers revenues via energy aware allocation policies"
    - "on allocation policies for power and performance"

Connected through hyperedge HE-4 (induced by source paper "base station on off switching in 5g wireless networks approaches and challenges"):
  with members:
    - "boost base station on off switching strategy for energy efficient massive mimo hetnets"
    - "green 5g heterogeneous networks through dynamic small cell operation"
    - "how many small cells can be turned off via vertical offloading under a separation architecture"
    - "what will 5g be"
    - "base station sleeping and resource allocation in renewable energy powered cellular networks"
    - "adaptive power management for wireless base stations in a smart grid environment"

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)