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: "big data computing and clouds"
  Abstract: This paper discusses approaches and environments for carrying out analytics on Clouds for Big Data applications. It revolves around four important areas of analytics and Big Data, namely (i) data management and supporting architectures; (ii) model development and scoring; (iii) visualisation and user interaction; and (iv) business models. Through a detailed survey, we identify possible gaps in technology and provide recommendations for the research community on future directions on Cloud-supported Big Data computing and analytics solutions. Survey of solutions for carrying out analytics and Big Data on Clouds.Identification of gaps in technology for Cloud-based analytics.Recommendations of research directions for Cloud-based analytics and Big Data.

Connected through hyperedge HE-1 (induced by source paper "authentication access control privacy threats and trust management towards securing fog computing environments a review"):
  with members:
    - "user s privacy in recommendation systems applying online social network data a survey and taxonomy"
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "fogbus a blockchain based lightweight framework for edge and fog computing"
    - "fog computing survey of trends architectures requirements and research directions"
    - "blockchain in internet of things challenges and solutions"
    - "combining ensemble methods and social network metrics for improving accuracy of ocsvm on intrusion detection in scada systems"
    - "non stationary resource allocation policies for delay constrained video streaming application to video over internet of things enabled networks"

Connected through hyperedge HE-2 (induced by source paper "storage solutions for big data systems a qualitative study and comparison"):
  with members:
    - "a billion updates per second using 30 000 hierarchical in memory d4m databases"
    - "foundationdb record layer a multi tenant structured datastore"
    - "hadoop perfect file a fast access container for small files with direct in disc metadata access"
    - "decentralized search on decentralized web"
    - "effects of storage heterogeneity in distributed cache systems"
    - "database as a service current issues and its future"
    - "chain of trust can trusted hardware help scaling blockchains"
    - "towards scaling blockchain systems via sharding"

Connected through hyperedge HE-3 (induced by source paper "bivariate cluster and suitability analysis of nosql solutions for different application areas"):
  with members:
    - "a billion updates per second using 30 000 hierarchical in memory d4m databases"
    - "foundationdb record layer a multi tenant structured datastore"
    - "effects of storage heterogeneity in distributed cache systems"
    - "database as a service current issues and its future"
    - "polypus a big data self deployable architecture for microblogging text extraction and real time sentiment analysis"
    - "a stitch in time saves nine sparql querying of property graphs using gremlin traversals"
    - "blocktag design and applications of a tagging system for blockchain analysis"
    - "g core a core for future graph query languages"

Connected through hyperedge HE-4 (induced by source paper "hpc cloud for scientific and business applications taxonomy vision and research challenges"):
  with members:
    - "in datacenter performance analysis of a tensor processing unit"
    - "about the suitability of clouds in high performance computing"
    - "sla aware interactive workflow assistant for hpc parameter sweeping experiments"
    - "job placement advisor based on turnaround predictions for hpc hybrid clouds"
    - "tensorflow a system for large scale machine learning"
    - "multi cloud resource provisioning with aneka a unified and integrated utilisation of microsoft azure and amazon ec2 instances"
    - "high performance cloud computing a view of scientific applications"
    - "the anatomy of the grid enabling scalable virtual organizations"

Connected through hyperedge HE-5 (induced by source paper "analytics for the internet of things a survey"):
  with members:
    - "middleware technologies for cloud of things a survey"
    - "context aware computing for the internet of things a survey"
    - "graphx unifying data parallel and graph parallel analytics"
    - "context aware sensor search selection and ranking model for internet of things middleware"
    - "querying over federated sparql endpoints a state of the art survey"
    - "the cloud adoption toolkit supporting cloud adoption decisions in the enterprise"

Connected through hyperedge HE-6 (induced by source paper "fog computing survey of trends architectures requirements and research directions"):
  with members:
    - "fog computing a taxonomy survey and future directions"
    - "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"
    - "demystifying fog computing characterizing architectures applications and abstractions"
    - "fog computing principles architectures and applications"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-7 (induced by source paper "internet of things iot and cloud computing enabled disaster management"):
  with members:
    - "cross layer multi cloud real time application qos monitoring and benchmarking as a service framework"
    - "the anatomy of big data computing"
    - "multi cloud resource provisioning with aneka a unified and integrated utilisation of microsoft azure and amazon ec2 instances"
    - "a cloud infrastructure service recommendation system for optimizing real time qos provisioning constraints"
    - "exploiting social navigation"

Connected through hyperedge HE-8 (induced by source paper "resource management and scheduling for big data applications in cloud computing environments"):
  with members:
    - "optex a deadline aware cost optimization model for spark"
    - "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)