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 "monetary cost optimizations for hosting workflow as a service in iaas clouds"):
  Abstract: Recently, we have witnessed workflows from science and other data-intensive applications emerging on Infrastructure-asa-Service (IaaS) clouds, and many workflow service providers offering workflow as a service (WaaS). The major concern of WaaS providers is to minimize the monetary cost of executing workflows in the IaaS cloud. While there have been previous studies on this concern, most of them assume static task execution time and static pricing scheme, and have the QoS notion of satisfying a deterministic deadline. However, cloud environment is dynamic, with performance dynamics caused by the interference from concurrent executions and price dynamics like spot prices offered by Amazon EC2. Therefore, we argue that WaaS providers should have the notion of offering probabilistic performance guarantees for individual workflows on IaaS clouds. We develop a probabilistic scheduling framework called Dyna to minimize the monetary cost while offering probabilistic deadline guarantees. The framework includes an A*-based instance configuration method for performance dynamics, and a hybrid instance configuration refinement for utilizing spot instances. Experimental results with three real-world scientific workflow applications on Amazon EC2 demonstrate (1) the accuracy of our framework on satisfying the probabilistic deadline guarantees required by the users; (2) the effectiveness of our framework on reducing monetary cost in comparison with the existing approaches.

Includes members:
  Member "a taxonomy and survey on escience as a service in the cloud":
    also connected through other hyperedges:
      (none)
  Member "performance measurement of cloud computing services":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "recent developments in cloud based systems state of art")
  Member "reliable provisioning of spot instances for compute intensive applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "characterizing application scheduling on edge fog and cloud computing resources")

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.DC(Distributed, Parallel, and Cluster Computing)