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 "incentme effective mechanism design to stimulate crowdsensing participants with uncertain mobility"):
  Abstract: Mobile crowdsensing harnesses the sensing power of modern smartphones to collect and analyze data beyond the scale of what was previously possible. In a mobile crowdsensing system, it is paramount to incentivize smartphone users to provide sensing services in a timely and reliable manner. Given sensed information is often valid for a limited period of time, the capability of smartphone users to execute sensing tasks largely depends on their mobility, which is often uncertain. For this reason, in this paper we propose IncentMe, a framework that solves this fundamental problem by leveraging game-theoretical reverse auction mechanism design. After demonstrating that the proposed problem is NP-hard, we derive two mechanisms that are parallelizable and achieve higher approximation ratio than existing work. IncentMe has been extensively evaluated on a road traffic monitoring application implemented using mobility traces of taxi cabs in San Francisco, Rome, and Beijing. Results demonstrate that the mechanisms in IncentMe outperform prior work by improving the efficiency in recruiting participants by 30%.

Includes members:
  Member "securing the internet of things in the age of machine learning and software defined networking":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "security privacy in iot using machine learning blockchain threats countermeasures")
  Member "quality of information in mobile crowdsensing survey and research challenges":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a novel methodology for designing policies in mobile crowdsensing systems")
  Member "taskme multi task allocation in mobile crowd sensing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "crowdos a ubiquitous operating system for crowdsourcing and mobile crowd sensing")
  Member "incentive mechanisms for participatory sensing survey and research challenges":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a novel methodology for designing policies in mobile crowdsensing systems")
  Member "mining users significant driving routes with low power sensors":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "systematic classification of side channel attacks a case study for mobile devices")
  Member "on the approximability of budget feasible mechanisms":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "budget feasible mechanism design for non monotone submodular objectives offline and online")
  Member "budget feasible mechanisms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "budget feasible mechanism design for non monotone submodular objectives offline and online")

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)