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: "scylla a mesos framework for container based mpi jobs"
  Abstract: Open source cloud technologies provide a wide range of support for creating customized compute node clusters to schedule tasks and managing resources. In cloud infrastructures such as Jetstream and Chameleon, which are used for scientific research, users receive complete control of the Virtual Machines (VM) that are allocated to them. Importantly, users get root access to the VMs. This provides an opportunity for HPC users to experiment with new resource management technologies such as Apache Mesos that have proven scalability, flexibility, and fault tolerance. To ease the development and deployment of HPC tools on the cloud, the containerization technology has matured and is gaining interest in the scientific community. In particular, several well known scientific code bases now have publicly available Docker containers. While Mesos provides support for Docker containers to execute individually, it does not provide support for container inter-communication or orchestration of the containers for a parallel or distributed application. In this paper, we present the design, implementation, and performance analysis of a Mesos framework, Scylla, which integrates Mesos with Docker Swarm to enable orchestration of MPI jobs on a cluster of VMs acquired from the Chameleon cloud [1]. Scylla uses Docker Swarm for communication between containerized tasks (MPI processes) and Apache Mesos for resource pooling and allocation. Scylla allows a policy-driven approach to determine how the containers should be distributed across the nodes depending on the CPU, memory, and network throughput requirement for each application.

Connected through hyperedge HE-1 (induced by source paper "tromino demand and drf aware multi tenant queue manager for apache mesos cluster"):
  with members:
    - "evaluation of docker containers for scientific workloads in the cloud"
    - "exploring the fairness and resource distribution in an apache mesos environment"
    - "multicloud resource management using apache mesos with apache airavata"
    - "r storm resource aware scheduling in storm"

Connected through hyperedge HE-2 (induced by source paper "exploring the fairness and resource distribution in an apache mesos environment"):
  with members:
    - "dominant resource fairness in cloud computing systems with heterogeneous servers"

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.PF(Performance)