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 "on modeling dependency between mapreduce configuration parameters and total execution time"):
  Abstract: In this paper, we propose an analytical method to model the dependency between configuration parameters and total execution time of Map-Reduce applications. Our approach has three key phases: profiling, modeling, and prediction. In profiling, an application is run several times with different sets of MapReduce configuration parameters to profile the execution time of the application on a given platform. Then in modeling, the relation between these parameters and total execution time is modeled by multivariate linear regression. Among the possible configuration parameters, two main parameters have been used in this study: the number of Mappers, and the number of Reducers. For evaluation, two standard applications (WordCount, and Exim Mainlog parsing) are utilized to evaluate our technique on a 4-node MapReduce platform.

Includes members:
  Member "a task based sensor centeric model for overall energy consumption":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a primarily survey on energy efficiency in cloud and distributed computing systems")
  Member "on using pattern matching algorithms in mapreduce applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "statistical analysis to extract effective parameters on overall energy consumption of wireless sensor network wsn")
  Member "modeling overall energy consumption in wireless sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "data gathering scheme for wireless sensornetworks using a single mobile element")
  Member "a study on modeling of dependency between configuration parameters and overall energy consumption in wireless sensor network wsn":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a primarily survey on energy efficiency in cloud and distributed computing systems")
  Member "some observations on optimal frequency selection in dvfs based energy consumption minimization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "energy efficiency in wireless sensor networks")

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)