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: "foggis fog computing for geospatial big data analytics"
  Abstract: Cloud Geographic Information Systems (GIS) has emerged as a tool for analysis, processing and transmission of geospatial data. The Fog computing is a paradigm where Fog devices help to increase throughput and reduce latency at the edge of the client. This paper developed a Fog-based framework named Fog GIS for mining analytics from geospatial data. We built a prototype using Intel Edison, an embedded microprocessor. We validated the FogGIS by doing preliminary analysis. including compression, and overlay analysis. Results showed that Fog computing hold a great promise for analysis of geospatial data. We used several open source compression techniques for reducing the transmission to the cloud.

Connected through hyperedge HE-1 (induced by source paper "challenges in designing edge based middlewares for the internet of things a survey"):
  with members:
    - "cefiot a fault tolerant iot architecture for edge and cloud"
    - "fogstore toward a distributed data store for fog computing"
    - "distributed scheduling of event analytics across edge and cloud"
    - "task allocation for distributed stream processing"
    - "cloud4iot a heterogeneous distributed and autonomic cloud platform for the iot"

Connected through hyperedge HE-2 (induced by source paper "fog computing in medical internet of things architecture implementation and applications"):
  with members:
    - "fog assisted wiot a smart fog gateway for end to end analytics in wearable internet of things"
    - "bigear inferring the ambient and emotional correlates from smartphone based acoustic big data"
    - "harmonic sum based method for heart rate estimation using ppg signals affected with motion artifacts"
    - "fit a fog computing device for speech teletreatments"
    - "echowear smartwatch technology for voice and speech treatments of patients with parkinson s disease"
    - "a multi smartwatch system for assessing speech characteristics of people with dysarthria in group settings"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-3 (induced by source paper "fog computing based sdi framework for mineral resources information infrastructure management in india"):
  with members:
    - "fog assisted wiot a smart fog gateway for end to end analytics in wearable internet of things"
    - "fog computing in medical internet of things architecture implementation and applications"
    - "comparative analysis of spatialhadoop and geospark for geospatial big data analytics"
    - "fit a fog computing device for speech teletreatments"
    - "fog computing principles architectures and applications"
    - "echowear smartwatch technology for voice and speech treatments of patients with parkinson s disease"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-4 (induced by source paper "soa fog secure service oriented edge computing architecture for smart health big data analytics"):
  with members:
    - "fog assisted wiot a smart fog gateway for end to end analytics in wearable internet of things"
    - "fog computing for sustainable smart cities a survey"
    - "smart fog fog computing framework for unsupervised clustering analytics in wearable internet of things"
    - "fog computing in medical internet of things architecture implementation and applications"
    - "comparative analysis of spatialhadoop and geospark for geospatial big data analytics"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-5 (induced by source paper "foglearn leveraging fog based machine learning for smart system big data analytics"):
  with members:
    - "fog computing in medical internet of things architecture implementation and applications"
    - "comparative analysis of spatialhadoop and geospark for geospatial big data analytics"
    - "fog computing principles architectures and applications"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-6 (induced by source paper "fair a hadoop based hybrid model for faculty information retrieval system"):
  with members:
    - "comparative analysis of spatialhadoop and geospark for geospatial big data analytics"
    - "fit a fog computing device for speech teletreatments"
    - "mllib machine learning in apache spark"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-7 (induced by source paper "foggrid leveraging fog computing for enhanced smart grid network"):
  with members:
    - "fog computing in medical internet of things architecture implementation and applications"
    - "network function virtualization state of the art and research challenges"

Connected through hyperedge HE-8 (induced by source paper "comparative analysis of spatialhadoop and geospark for geospatial big data analytics"):
  with members:
    - "bigear inferring the ambient and emotional correlates from smartphone based acoustic big data"
    - "harmonic sum based method for heart rate estimation using ppg signals affected with motion artifacts"
    - "fit a fog computing device for speech teletreatments"
    - "echowear smartwatch technology for voice and speech treatments of patients with parkinson s disease"
    - "a multi smartwatch system for assessing speech characteristics of people with dysarthria in group settings"
    - "fog data enhancing telehealth big data through fog computing"
    - "the anatomy of big data computing"

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.DC(Distributed, Parallel, and Cluster Computing)