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: "toward hierarchical mobile edge computing an auction based profit maximization approach"
  Abstract: The multitiered concept of Internet of Things (IoT) devices, cloudlets, and clouds is facilitating a user-centric IoT. However, in such three tier network, it is still desirable to investigate efficient strategies to offer the computing, storage, and communications resources to the users. To this end, this paper proposes a new hierarchical model by introducing the concept of  field ,  shallow , and  deep  cloudlets where the cloudlet tier itself is designed in three hierarchical levels based on the principle of LTE-advanced backhaul network. Accordingly, we explore a two time scale approach in which the computing resources are offered in an auction-based profit maximization manner and then the communications resources are allocated to satisfy the users’ quality of service.

Connected through hyperedge HE-1 (induced by source paper "all one needs to know about fog computing and related edge computing paradigms a complete survey"):
  with members:
    - "pcamp performance comparison of machine learning packages on the edges"
    - "are fpgas suitable for edge computing"
    - "cabaret leveraging recommendation systems for mobile edge caching"
    - "edge intelligence on demand deep learning model co inference with device edge synergy"
    - "fog computing a taxonomy survey and future directions"
    - "data analytics service composition and deployment on edge devices"
    - "live service migration in mobile edge clouds"
    - "on reducing iot service delay via fog offloading"

Connected through hyperedge HE-2 (induced by source paper "learning based priority pricing for job offloading in mobile edge computing"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "latency and reliability aware task offloading and resource allocation for mobile edge computing"
    - "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"
    - "power delay tradeoff in multi user mobile edge computing systems"
    - "decentralized computation offloading game for mobile cloud computing"

Connected through hyperedge HE-3 (induced by source paper "joint dynamic pricing and radio resource allocation framework for iot services"):
  with members:
    - "adaptive and resilient revenue maximizing dynamic resource allocation and pricing for cloud enabled iot systems"
    - "computing resource allocation in three tier iot fog networks a joint optimization approach combining stackelberg game and matching"
    - "market model and optimal pricing scheme of big data and internet of things iot"
    - "mobile data transactions in device to device communication networks pricing and auction"
    - "multiobjective signal processing optimization the way to balance conflicting metrics in 5g systems"
    - "price based resource allocation for spectrum sharing femtocell networks a stackelberg game approach"

Connected through hyperedge HE-4 (induced by source paper "follow me at the edge mobility aware dynamic service placement for mobile edge computing"):
  with members:
    - "edge intelligence on demand deep learning model co inference with device edge synergy"
    - "efficient resource allocation for on demand mobile edge cloud computing"
    - "exploiting massive d2d collaboration for energy efficient mobile edge computing"
    - "emm energy aware mobility management for mobile edge computing in ultra dense networks"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "dynamic service placement for mobile micro clouds with predicted future costs"
    - "a non stochastic learning approach to energy efficient mobility management"
    - "dynamic service migration in mobile edge clouds"

Connected through hyperedge HE-5 (induced by source paper "auction mechanisms in cloud fog computing resource allocation for public blockchain networks"):
  with members:
    - "towards blockchain based auditable storage and sharing of iot data"
    - "performance analysis and application of mobile blockchain"
    - "when mobile blockchain meets edge computing"
    - "optimal pricing based edge computing resource management in mobile blockchain"
    - "hardening stratum the bitcoin pool mining protocol"
    - "social welfare maximization auction in edge computing resource allocation for mobile blockchain"
    - "optimal auction for edge computing resource management in mobile blockchain networks a deep learning approach"
    - "untangling blockchain a data processing view of blockchain systems"

Connected through hyperedge HE-6 (induced by source paper "edge computing aware noma for 5g networks"):
  with members:
    - "non orthogonal random access nora for 5g networks"
    - "joint subcarrier and cpu time allocation for mobile edge computing"
    - "dynamic user clustering and power allocation for uplink and downlink non orthogonal multiple access noma systems"
    - "uplink non orthogonal multiple access for 5g wireless networks"
    - "joint optimization of radio resources and code partitioning in mobile cloud computing"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-7 (induced by source paper "hierarchical capacity provisioning for fog computing"):
  with members:
    - "profit maximization for geographically dispersed green data centers"
    - "green cloudlet network a distributed green mobile cloud network"
    - "primal profit maximization avatar placement for mobile edge computing"
    - "an auction mechanism for resource allocation in mobile cloud computing systems"

Connected through hyperedge HE-8 (induced by source paper "joint spectrum allocation and structure optimization in green powered heterogeneous cognitive radio networks"):
  with members:
    - "backhaul aware user association and resource allocation for energy constrained hetnets"
    - "wireless networks with energy harvesting and power transfer joint power and time allocation"
    - "optimal cooperative power allocation for energy harvesting enabled relay networks"
    - "joint spectrum and power allocation for multi node cooperative wireless systems"
    - "on green energy powered cognitive radio networks"
    - "qos aware base station selections for distributed mimo links in broadband wireless networks"
    - "maximizing system throughput by cooperative sensing in cognitive radio networks"

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.NI(Networking and Internet Architecture)