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 "scalable mobile crowdsensing via peer to peer data sharing"):
  Abstract: Mobile crowdsensing (MCS) is a new paradigm of sensing by taking advantage of the rich embedded sensors of mobile user devices. However, the traditional server-client MCS architecture often suffers from the high operational cost on the centralized server (e.g., for storing and processing massive data), hence the poor scalability. Peer-to-peer (P2P) data sharing can effectively reduce the server's cost by leveraging the user devices' computation and storage resources. In this work, we propose a novel P2P-based MCS architecture, where the sensing data is saved and processed in user devices locally and shared among users in a P2P manner. To provide necessary incentives for users in such a system, we propose a quality-aware data sharing market, where the users who sense data can sell data to others who request data but not want to sense the data by themselves. We analyze the user behavior dynamics from the game-theoretic perspective, and characterize the existence and uniqueness of the game equilibrium. We further propose best response iterative algorithms to reach the equilibrium with provable convergence. Our simulations show that the P2P data sharing can greatly improve the social welfare, especially in the model with a high transmission cost and a low trading price.

Includes members:
  Member "economic analysis of crowdsourced wireless community networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi cap optimization for wireless data plans with time flexibility")
  Member "dynamic routing for social information sharing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "crowd mecs a novel crowdsourcing framework for mobile edge caching and sharing")
  Member "an integrated spectrum and information market for green cognitive communications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi cap optimization for wireless data plans with time flexibility")
  Member "providing long term participation incentive in participatory sensing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "small profits and quick returns an incentive mechanism design for iot based crowdsourcing under continuous platform competition")
  Member "a game theoretic analysis of user behaviors in crowdsourced wireless community networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "performance bound analysis for crowdsourced mobile video streaming")
  Member "mine gold to deliver green cognitive communications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "duopoly competition for mobile data plans with time flexibility")
  Member "hysim a hybrid spectrum and information market for tv white space networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a comprehensive survey on networking over tv white spaces")
  Member "distributed time sensitive task selection in mobile crowdsensing":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "trajectory design for multiple uav assisted wireless networks")

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.GT(Computer Science and Game Theory)