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 efficient location and activity aware on demand mobile distributed sensing platform for sensing as a service in iot clouds"
  Abstract: The Internet of Things (IoT) envisions billions of sensors deployed around us and connected to the Internet, where the mobile crowd sensing technologies are widely used to collect data in different contexts of the IoT paradigm. Due to the popularity of Big Data technologies, processing and storing large volumes of data have become easier than ever. However, large-scale data management tasks still require significant amounts of resources that can be expensive regardless of whether they are purchased or rented (e.g., pay-as-you-go infrastructure). Further, not everyone is interested in such large-scale data collection and analysis. More importantly, not everyone has the financial and computational resources to deal with such large volumes of data. Therefore, a timely need exists for a cloud-integrated mobile crowd sensing platform that is capable of capturing sensors data, on-demand, based on conditions enforced by the data consumers. In this paper, we propose a context-aware, specifically, location and activity-aware mobile sensing platform called context-aware mobile sensor data engine (C-MOSDEN) for the IoT domain. We evaluated the proposed platform using three real-world scenarios that highlight the importance of  selective sensing . The computational effectiveness and efficiency of the proposed platform are investigated and are used to highlight the advantages of context-aware selective sensing.

Connected through hyperedge HE-1 (induced by source paper "a spatial temporal correlation approach for data reduction in cluster based sensor networks"):
  with members:
    - "a hybrid approach for data analytics for internet of things"
    - "efficient opportunistic sensing using mobile collaborative platform mosden"

Connected through hyperedge HE-2 (induced by source paper "fog computing for sustainable smart cities a survey"):
  with members:
    - "fog networking an overview on research opportunities"
    - "a survey of systems for massive stream analytics"
    - "cloudrone micro clouds in the sky"
    - "applying seamful design in location based mobile museum applications"
    - "fog data enhancing telehealth big data through fog computing"
    - "big data privacy in the internet of things era"
    - "the emerging internet of things marketplace from an industrial perspective a survey"
    - "a survey on internet of things from industrial market perspective"

Connected through hyperedge HE-3 (induced by source paper "middleware technologies for cloud of things a survey"):
  with members:
    - "context aware computing for the internet of things a survey"
    - "context aware sensor search selection and ranking model for internet of things middleware"
    - "mosden an internet of things middleware for resource constrained mobile devices"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-4 (induced by source paper "privacy by design framework for assessing internet of things applications and platforms"):
  with members:
    - "analytics as a service in a multi cloud environment through semantically enabled hierarchical data processing"
    - "big data privacy in the internet of things era"
    - "the emerging internet of things marketplace from an industrial perspective a survey"
    - "iprivacy a distributed approach to privacy on the cloud"
    - "context aware computing for the internet of things a survey"
    - "privacy design strategies"

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)