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: "reliable provisioning of spot instances for compute intensive applications"
  Abstract: Cloud computing providers are now offering their unused resources for leasing in the spot market, which has been considered the first step towards a full-fledged market economy for computational resources. Spot instances are virtual machines (VMs) available at lower prices than their standard on-demand counterparts. These VMs will run for as long as the current price is lower than the maximum bid price users are willing to pay per hour. Spot instances have been increasingly used for executing compute-intensive applications. In spite of an apparent economical advantage, due to an intermittent nature of biddable resources, application execution times may be prolonged or they may not finish at all. This paper proposes a resource allocation strategy that addresses the problem of running compute-intensive jobs on a pool of intermittent virtual machines, while also aiming to run applications in a fast and economical way. To mitigate potential unavailability periods, a multifaceted fault-aware resource provisioning policy is proposed. Our solution employs price and runtime estimation mechanisms, as well as three fault tolerance techniques, namely checkpointing, task duplication and migration. We evaluate our strategies using trace-driven simulations, which take as input real price variation traces, as well as an application trace from the Parallel Workload Archive. Our results demonstrate the effectiveness of executing applications on spot instances, respecting QoS constraints, despite occasional failures.

Connected through hyperedge HE-1 (induced by source paper "characterizing application scheduling on edge fog and cloud computing resources"):
  with members:
    - "violet a large scale virtual environment for internet of things"
    - "adaptive energy aware scheduling of dynamic event analytics across edge and cloud resources"
    - "slaq quality driven scheduling for distributed machine learning"
    - "arm wrestling with big data a study of commodity arm64 server for big data workloads"
    - "a manifesto for future generation cloud computing research directions for the next decade"
    - "demystifying fog computing characterizing architectures applications and abstractions"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "big data and fog computing"

Connected through hyperedge HE-2 (induced by source paper "an efficient cloud scheduler design supporting preemptible instances"):
  with members:
    - "resource provisioning in science clouds requirements and challenges"
    - "improved cloud resource allocation how indigo datacloud is overcoming the current limitations in cloud schedulers"
    - "efficient image deployment in cloud environments"
    - "application centric resource provisioning for amazon ec2 spot instances"
    - "provisioning spot market cloud resources to create cost effective virtual clusters"
    - "cloud computing and grid computing 360 degree compared"

Connected through hyperedge HE-3 (induced by source paper "resource provisioning in science clouds requirements and challenges"):
  with members:
    - "the anatomy of big data computing"
    - "phenomenology tools on cloud infrastructures using openstack"
    - "patience aware scheduling for cloud services freeing users from the chains of boredom"
    - "maximizing cloud providers revenues via energy aware allocation policies"
    - "workload classification a software energy measurement for efficient scheduling on private cloud platforms"
    - "provisioning spot market cloud resources to create cost effective virtual clusters"
    - "energy efficient management of data center resources for cloud computing a vision architectural elements and open challenges"
    - "cloud computing and grid computing 360 degree compared"

Connected through hyperedge HE-4 (induced by source paper "spot pricing in the cloud ecosystem a comparative investigation"):
  with members:
    - "on evaluating commercial cloud services a systematic review"
    - "application centric resource provisioning for amazon ec2 spot instances"
    - "provisioning spot market cloud resources to create cost effective virtual clusters"
    - "cloud computing and grid computing 360 degree compared"

Connected through hyperedge HE-5 (induced by source paper "monetary cost optimizations for hosting workflow as a service in iaas clouds"):
  with members:
    - "a taxonomy and survey on escience as a service in the cloud"
    - "performance measurement of cloud computing services"

Connected through hyperedge HE-6 (induced by source paper "application centric resource provisioning for amazon ec2 spot instances"):
  with members:
    - "market oriented cloud computing vision hype and reality for delivering it services as computing utilities"

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.DC(Distributed, Parallel, and Cluster Computing)