human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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.

Includes members:
  Member "the emerging internet of things marketplace from an industrial perspective a survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "minimizing the age of information of cognitive radio based iot systems under a collision constraint")
  Member "a survey on internet of things from industrial market perspective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a throughput and energy efficiency scheme for unlicensed massive machine type communications")
  Member "context aware dynamic discovery and configuration of things in smart environments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fog computing for sustainable smart cities a survey")
  Member "semantic driven configuration of internet of things middleware":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "composable industrial internet applications for tiered architectures")
  Member "efficient opportunistic sensing using mobile collaborative platform mosden":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "maximizing clearance rate by penalizing redundant task assignment in mobile crowdsensing auctions")
  Member "mosden an internet of things middleware for resource constrained mobile devices":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "middleware technologies for cloud of things a survey")
  Member "sensing as a service and big data":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "big data in iot systems")
  Member "sensing as a service model for smart cities supported by internet of things":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "fog computing applications taxonomy and requirements")

Question: Please tell me which class the source paper 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)