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: "fogbus a blockchain based lightweight framework for edge and fog computing"
  Abstract: The requirement of supporting both latency sensitive and computing intensive Internet of Things (IoT) applications is consistently boosting the necessity for integrating Edge, Fog and Cloud infrastructure. Although there are a number of real-world frameworks attempt to support such integration, they have many limitations from various perspectives including platform independence, security, resource management and multi-application assistance. To address these limitations, we propose a simplified but effective framework, named FogBus for facilitating end-to-end IoT-Fog(Edge)-Cloud integration. FogBus offers a platform independent interface to IoT applications and computing instances for execution and interaction. It not only assists developers in building applications but also helps users in running multiple applications at a time and service providers to manage their resources. In addition, FogBus applies Blockchain, authentication and encryption techniques to secure operations on sensitive data. Because of its lightweight and cross platform software systems, it is easy to deploy, scalable and cost e_cient. We demonstrate the effectiveness of our framework by creating a computing environment with it that integrates finger pulse oximeter as IoT devices with Smartphone-based gateway and Raspberry Pi-based Fog nodes for Sleep Apnea analysis. We also run several experiments on this computing environment varying FogBus settings. The experimental results show that different FogBus settings can improve latency, energy, network and CPU usage of the computing infrastructure.

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"
    - "fog computing survey of trends architectures requirements and research directions"
    - "blockchain in internet of things challenges and solutions"
    - "big data computing and clouds"
    - "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 "healthfog an ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated iot and fog computing environments"):
  with members:
    - "edgelens deep learning based object detection in integrated iot fog and cloud computing environments"
    - "scalable and accurate deep learning for electronic health records"
    - "fog assisted wiot a smart fog gateway for end to end analytics in wearable internet of things"
    - "foglearn leveraging fog based machine learning for smart system big data analytics"
    - "gram graph based attention model for healthcare representation learning"
    - "aneka a software platform for net based cloud computing"

Connected through hyperedge HE-3 (induced by source paper "transformative effects of iot blockchain and artificial intelligence on cloud computing evolution vision trends and open challenges"):
  with members:
    - "healthfog an ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated iot and fog computing environments"
    - "a deep learning based approach to vm behavior identification in cloud systems"
    - "edgelens deep learning based object detection in integrated iot fog and cloud computing environments"
    - "bottlenet a deep learning architecture for intelligent mobile cloud computing services"
    - "cloud chaser real time deep learning computer vision on low computing power devices"
    - "a survey on the security of blockchain systems"
    - "container based cluster orchestration systems a taxonomy and future directions"
    - "sustainable cloud computing foundations and future directions"

Connected through hyperedge HE-4 (induced by source paper "edgelens deep learning based object detection in integrated iot fog and cloud computing environments"):
  with members:
    - "salient object detection a survey"
    - "yolov3 an incremental improvement"
    - "fog assisted wiot a smart fog gateway for end to end analytics in wearable internet of things"
    - "distributed deep neural networks over the cloud the edge and end devices"
    - "you only look once unified real time object detection"
    - "aneka a software platform for net based cloud 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)