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: "distributed time sensitive task selection in mobile crowdsensing"
  Abstract: With the rich set of embedded sensors installed in smartphones and the large number of mobile users, we witness the emergence of many innovative commercial mobile crowdsensing applications that combine the power of mobile technology with crowdsourcing to deliver time-sensitive and location-dependent information to their customers. Motivated by these real-world applications, we consider the task selection problem for heterogeneous users with different initial locations, movement costs, movement speeds, and reputation levels. Computing the social surplus maximization task allocation turns out to be an NP-hard problem. Hence we focus on the distributed case, and propose an asynchronous and distributed task selection (ADTS) algorithm to help the users plan their task selections on their own. We prove the convergence of the algorithm, and further characterize the computation time for users' updates in the algorithm. Simulation results suggest that the ADTS scheme achieves the highest Jain's fairness index and coverage comparing with several benchmark algorithms, while yielding similar user payoff to a greedy centralized benchmark. Finally, we illustrate how mobile users coordinate under the ADTS scheme based on some practical movement time data derived from Google Maps.

Connected through hyperedge HE-1 (induced by source paper "trajectory design for multiple uav assisted wireless networks"):
  with members:
    - "adaptive deployment for uav aided communication networks"
    - "energy minimization for wireless communication with rotary wing uav"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges"
    - "placement optimization of uav mounted mobile base stations"
    - "dronecells improving 5g spectral efficiency using drone mounted flying base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "mobile unmanned aerial vehicles uavs for energy efficient internet of things communications"

Connected through hyperedge HE-2 (induced by source paper "maximizing clearance rate by penalizing redundant task assignment in mobile crowdsensing auctions"):
  with members:
    - "maximizing clearance rate of reputation aware auctions in mobile crowdsensing"
    - "efficient opportunistic sensing using mobile collaborative platform mosden"

Connected through hyperedge HE-3 (induced by source paper "fine grained user profiling for personalized task matching in mobile crowdsensing"):
  with members:
    - "a survey on truth discovery"

Connected through hyperedge HE-4 (induced by source paper "scalable mobile crowdsensing via peer to peer data sharing"):
  with members:
    - "economic analysis of crowdsourced wireless community networks"
    - "dynamic routing for social information sharing"
    - "an integrated spectrum and information market for green cognitive communications"
    - "providing long term participation incentive in participatory sensing"
    - "a game theoretic analysis of user behaviors in crowdsourced wireless community networks"
    - "mine gold to deliver green cognitive communications"
    - "hysim a hybrid spectrum and information market for tv white space networks"
    - "combining spot and futures markets a hybrid market approach to dynamic spectrum access"

Connected through hyperedge HE-5 (induced by source paper "data centric mobile crowdsensing"):
  with members:
    - "scalable mobile crowdsensing via peer to peer data sharing"
    - "two sided matching based cooperative spectrum sharing"
    - "economic analysis of crowdsourced wireless community networks"
    - "centurion incentivizing multi requester mobile crowd sensing"
    - "dynamic routing for social information sharing"
    - "providing long term participation incentive in participatory sensing"
    - "combining spot and futures markets a hybrid market approach to dynamic spectrum access"
    - "motivating smartphone collaboration in data acquisition and distributed computing"

Connected through hyperedge HE-6 (induced by source paper "reap an efficient incentive mechanism for reconciling aggregation accuracy and individual privacy in crowdsensing"):
  with members:
    - "the value of privacy strategic data subjects incentive mechanisms and fundamental limits"
    - "crowdsourcing with tullock contests a new perspective"
    - "redrawing the boundaries on purchasing data from privacy sensitive individuals"
    - "privacy and mechanism design"
    - "calibrating data to sensitivity in private data analysis"
    - "take it or leave it running a survey when privacy comes at a cost"
    - "approximately optimal auctions for selling privacy when costs are correlated with data"
    - "selling privacy at auction"

Connected through hyperedge HE-7 (induced by source paper "theseus incentivizing truth discovery in mobile crowd sensing systems"):
  with members:
    - "centurion incentivizing multi requester mobile crowd sensing"
    - "the value of privacy strategic data subjects incentive mechanisms and fundamental limits"
    - "providing long term participation incentive in participatory sensing"
    - "crowdsourcing with tullock contests a new perspective"
    - "truthful linear regression"
    - "linear regression as a non cooperative game"

Connected through hyperedge HE-8 (induced by source paper "technical report for user centric participatory sensing a game theoretic analysis"):
  with members:
    - "scalable mobile crowdsensing via peer to peer data sharing"
    - "a double auction mechanism for mobile crowd sensing with data reuse"
    - "mine gold to deliver green cognitive communications"

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.GT(Computer Science and Game Theory)