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: "r storm resource aware scheduling in storm"
  Abstract: The era of big data has led to the emergence of new systems for real-time distributed stream processing, e.g., Apache Storm is one of the most popular stream processing systems in industry today. However, Storm, like many other stream processing systems lacks an intelligent scheduling mechanism. The default round-robin scheduling currently deployed in Storm disregards resource demands and availability, and can therefore be inefficient at times. We present R-Storm (Resource-Aware Storm), a system that implements resource-aware scheduling within Storm. R-Storm is designed to increase overall throughput by maximizing resource utilization while minimizing network latency. When scheduling tasks, R-Storm can satisfy both soft and hard resource constraints as well as minimizing network distance between components that communicate with each other. We evaluate R-Storm on set of micro-benchmark Storm applications as well as Storm applications used in production at Yahoo! Inc. From our experimental results we conclude that R-Storm achieves 30-47% higher throughput and 69-350% better CPU utilization than default Storm for the micro-benchmarks. For the Yahoo! Storm applications, R-Storm outperforms default Storm by around 50% based on overall throughput. We also demonstrate that R-Storm performs much better when scheduling multiple Storm applications than default Storm.

Connected through hyperedge HE-1 (induced by source paper "a scheduling algorithm to maximize storm throughput in heterogeneous cluster"):
  with members:
    - "a survey of systems for massive stream analytics"
    - "a domain specific approach to high performance heterogeneous computing"

Connected through hyperedge HE-2 (induced by source paper "briskstream scaling data stream processing on shared memory multicore architectures"):
  with members:
    - "oltp on hardware islands"

Connected through hyperedge HE-3 (induced by source paper "model driven scheduling for distributed stream processing systems"):
  with members:
    - "benchmarking distributed stream processing platforms for iot applications"
    - "task allocation for distributed stream processing"
    - "drs dynamic resource scheduling for real time analytics over fast streams"
    - "benchmarking fast data platforms for the aadhaar biometric database"
    - "bigdatabench a big data benchmark suite from internet services"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-4 (induced by source paper "tromino demand and drf aware multi tenant queue manager for apache mesos cluster"):
  with members:
    - "scylla a mesos framework for container based mpi jobs"
    - "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"

Connected through hyperedge HE-5 (induced by source paper "henge intent driven multi tenant stream processing"):
  with members:
    - "slaq quality driven scheduling for distributed machine learning"
    - "drs dynamic resource scheduling for real time analytics over fast streams"
    - "when two choices are not enough balancing at scale in distributed stream processing"
    - "the power of both choices practical load balancing for distributed stream processing engines"

Connected through hyperedge HE-6 (induced by source paper "on sdn enabled online and dynamic bandwidth allocation for stream analytics"):
  with members:
    - "task allocation for distributed stream processing"
    - "software defined networking a comprehensive survey"

Connected through hyperedge HE-7 (induced by source paper "towards physiology aware dash bandwidth compliant prioritized clinical multimedia communication in ambulances"):
  with members:
    - "physiology aware rural ambulance routing"
    - "a mobile geo communication dataset for physiology aware dash in rural ambulance transport"
    - "a pathophysiological model driven communication for dynamic distributed medical best practice guidance systems"
    - "adaptive 360 vr video streaming divide and conquer"
    - "sink a middleware for synchronization of heterogeneous software interfaces"
    - "probe and adapt rate adaptation for http video streaming at scale"
    - "rate adaptation and admission control for video transmission with subjective quality constraints"

Connected through hyperedge HE-8 (induced by source paper "elasticutor rapid elasticity for realtime stateful stream processing"):
  with members:
    - "optimal operator state migration for elastic data stream processing"
    - "muppet mapreduce style processing of fast data"

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)