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: "resource management in cloud networking using economic analysis and pricing models a survey"
  Abstract: This paper presents a comprehensive literature review on applications of economic and pricing models for resource management in cloud networking. To achieve sustainable profit advantage, cost reduction, and flexibility in provisioning of cloud resources, resource management in cloud networking requires adaptive and robust designs to address many issues, e.g., resource allocation, bandwidth reservation, request allocation, and workload allocation. Economic and pricing models have received a lot of attention as they can lead to desirable performance in terms of social welfare, fairness, truthfulness, profit, user satisfaction, and resource utilization. This paper reviews applications of the economic and pricing models to develop adaptive algorithms and protocols for resource management in cloud networking. Besides, we survey a variety of incentive mechanisms using the pricing strategies in sharing resources in edge computing. In addition, we consider using pricing models in cloud-based Software Defined Wireless Networking (cloud-based SDWN). Finally, we highlight important challenges, open issues and future research directions of applying economic and pricing models to cloud networking

Connected through hyperedge HE-1 (induced by source paper "mobile edge computing a survey on architecture and computation offloading"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "online placement of multi component applications in edge computing environments"
    - "dynamic service placement for mobile micro clouds with predicted future costs"
    - "delay optimal computation task scheduling for mobile edge computing systems"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "multiuser resource allocation for mobile edge computation offloading"
    - "power delay tradeoff in multi user mobile edge computing systems"

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)