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: "sensor deployment with limited communication range in homogeneous and heterogeneous wireless sensor networks"
  Abstract: We study the heterogeneous wireless sensor networks (WSNs) and propose the necessary condition of the optimal sensor deployment. Similar to that in homogeneous WSNs, the necessary condition implies that every sensor node location should coincide with the centroid of its own optimal sensing region. Moreover, we discuss the dynamic sensor deployment in both homogeneous and heterogeneous WSNs with limited communication range for the sensor nodes. The purpose of sensor deployment is to improve sensing performance, reflected by distortion and coverage. We model the sensor deployment problem as a source coding problem with distortion reflecting sensing accuracy. Traditionally, coverage is the area covered by the sensor nodes. However, when the communication range is limited, a WSN may be divided into several disconnected sub-graphs. Under such a scenario, neither the conventional distortion nor the coverage represents the sensing performance as the collected data in disconnected sub-graphs cannot be communicated with the access point. By defining an appropriate distortion measure, we propose a Restrained Lloyd (RL) algorithm and a Deterministic Annealing (DA) algorithm to optimize sensor deployment in both homogeneous and heterogeneous WSNs. Our simulation results show that both DA and RL algorithms outperform the existing Lloyd algorithm when communication range is limited.

Connected through hyperedge HE-1 (induced by source paper "optimal deployments of uavs with directional antennas for a power efficient coverage"):
  with members:
    - "energy efficient resource allocation in uav enabled mobile edge computing networks"
    - "using quantization to deploy heterogeneous nodes in two tier wireless sensor networks"
    - "energy minimization for wireless communication with rotary wing uav"
    - "quantizers with parameterized distortion measures"
    - "reshaping cellular networks for the sky the major factors and feasibility"
    - "backhaul for low altitude uavs in urban environments"
    - "deployment and trajectory optimization for uavs a quantization theory approach"
    - "joint altitude and beamwidth optimization for uav enabled multiuser communications"

Connected through hyperedge HE-2 (induced by source paper "energy efficient node deployment in wireless ad hoc sensor networks"):
  with members:
    - "using quantization to deploy heterogeneous nodes in two tier wireless sensor networks"
    - "movement efficient sensor deployment in wireless sensor networks"

Connected through hyperedge HE-3 (induced by source paper "using quantization to deploy heterogeneous nodes in two tier wireless sensor networks"):
  with members:
    - "quantizers with parameterized distortion measures"

Connected through hyperedge HE-4 (induced by source paper "quantizers with parameterized distortion measures"):
  with members:
    - "backhaul for low altitude uavs in urban environments"
    - "deployment and trajectory optimization for uavs a quantization theory approach"
    - "joint altitude and beamwidth optimization for uav enabled multiuser communications"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"

Connected through hyperedge HE-5 (induced by source paper "movement efficient sensor deployment in wireless sensor networks with limited communication range"):
  with members:
    - "movement efficient sensor deployment in wireless sensor networks"
    - "algorithms on minimizing the maximum sensor movement for barrier coverage of a linear domain"

Connected through hyperedge HE-6 (induced by source paper "movement efficient sensor deployment in wireless sensor networks"):
  with members:
    - "algorithms on minimizing the maximum sensor movement for barrier coverage of a linear domain"

Connected through hyperedge HE-7 (induced by source paper "energy efficiency in two tiered wireless sensor networks"):
  with members:
    - "location aware cross tier coordinated multipoint transmission in two tier cellular 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)