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 "model driven scheduling for distributed stream processing systems"):
  Abstract: Abstract   Distributed Stream Processing Systems (DSPS) are “Fast Data” platforms that allow streaming applications to be composed and executed with low latency on commodity clusters and Clouds. Such applications are composed as a Directed Acyclic Graph (DAG) of tasks, with data parallel execution using concurrent task threads on distributed resource slots. Scheduling such DAGs for DSPS has two parts—allocation of threads and resources for a DAG, and mapping threads to resources. Existing schedulers often address just one of these, make the assumption that performance linearly scales, or use ad hoc empirical tuning at runtime. Instead, we propose model-driven techniques for both mapping and allocation that rely on low-overhead a priori performance modeling of tasks. Our scheduling algorithms are able to offer predictable and low resource needs that is suitable for elastic pay-as-you-go Cloud resources, support a high input rate through high VM utilization, and can be combined with other mapping approaches as well. These are validated for micro and application benchmarks, and compared with contemporary schedulers, for the Apache Storm DSPS.

Includes members:
  Member "benchmarking distributed stream processing platforms for iot applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an efficient and scalable privacy preserving algorithm for big data and data streams")
  Member "task allocation for distributed stream processing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "challenges in designing edge based middlewares for the internet of things a survey")
  Member "r storm resource aware scheduling in storm":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a scheduling algorithm to maximize storm throughput in heterogeneous cluster")
  Member "drs dynamic resource scheduling for real time analytics over fast streams":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey of big data machine learning applications optimization in cloud data centers and networks")
  Member "benchmarking fast data platforms for the aadhaar biometric database":
    also connected through other hyperedges:
      (none)
  Member "bigdatabench a big data benchmark suite from internet services":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "tlb and pagewalk performance in multicore architectures with large die stacked dram cache")
  Member "internet of things iot a vision architectural elements and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "neuromemristive circuits for edge computing a review")

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)