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: "era a framework for economic resource allocation for the cloud"
  Abstract: Cloud computing has reached significant maturity from a systems perspective, but currently deployed solutions rely on rather basic economics mechanisms that yield suboptimal allocation of the costly hardware resources. In this paper we present Economic Resource Allocation (ERA), a complete framework for scheduling and pricing cloud resources, aimed at increasing the efficiency of cloud resources usage by allocating resources according to economic principles. The ERA architecture carefully abstracts the underlying cloud infrastructure, enabling the development of scheduling and pricing algorithms independently of the concrete lower-level cloud infrastructure and independently of its concerns. Specifically, ERA is designed as a flexible layer that can sit on top of any cloud system and interfaces with both the cloud resource manager and with the users who reserve resources to run their jobs. The jobs are scheduled based on prices that are dynamically calculated according to the predicted demand. Additionally, ERA provides a key internal API to pluggable algorithmic modules that include scheduling, pricing and demand prediction. We provide a proof-of-concept software and demonstrate the effectiveness of the architecture by testing ERA over both public and private cloud systems -- Azure Batch of Microsoft and Hadoop/YARN. A broader intent of our work is to foster collaborations between economics and system communities. To that end, we have developed a simulation platform via which economics and system experts can test their algorithmic implementations.

Connected through hyperedge HE-1 (induced by source paper "online revenue maximization for server pricing"):
  with members:
    - "stability of service under time of use pricing"
    - "learning simple auctions"
    - "truthful online scheduling with commitments"
    - "the sample complexity of revenue maximization"
    - "the pseudo dimension of near optimal auctions"
    - "combinatorial auctions via posted prices"

Connected through hyperedge HE-2 (induced by source paper "on the cluster admission problem for cloud computing"):
  with members:
    - "overcommitment in cloud services bin packing with chance constraints"
    - "truthful online scheduling with commitments"
    - "fixed and market pricing for cloud services"
    - "fair allocation without trade"
    - "no justified complaints on fair sharing of multiple resources"
    - "finding approximate pomdp solutions through belief compression"
    - "nonapproximability results for partially observable markov decision processes"

Connected through hyperedge HE-3 (induced by source paper "a data driven approach to dynamically adjust resource alocation for compute clusters"):
  with members:
    - "don t cry over spilled records memory elasticity of data parallel applications and its application to cluster scheduling"
    - "flexible scheduling of distributed analytic applications"
    - "revisiting size based scheduling with estimated job sizes"
    - "variational gaussian process state space models"
    - "os assisted task preemption for hadoop"
    - "psbs practical size based scheduling"

Connected through hyperedge HE-4 (induced by source paper "pricing for online resource allocation intervals and paths"):
  with members:
    - "stability of service under time of use pricing"
    - "simple mechanisms for subadditive buyers via duality"
    - "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs"
    - "mechanism design for subadditive agents via an ex ante relaxation"
    - "truthful online scheduling with commitments"
    - "the invisible hand of dynamic market pricing"
    - "simple mechanisms for a subadditive buyer and applications to revenue monotonicity"
    - "a simple and approximately optimal mechanism for an additive buyer"

Connected through hyperedge HE-5 (induced by source paper "truth and regret in online scheduling"):
  with members:
    - "stability of service under time of use pricing"
    - "truthful online scheduling with commitments"
    - "bandits with switching costs t 2 3 regret"
    - "satzilla portfolio based algorithm selection for sat"
    - "optimal mechansim design and money burning"

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)