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 "a survey of distributed data aggregation algorithms"):
  Abstract: Distributed data aggregation is an important task, allowing the decentralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting values result from the distributed computation of functions like COUNT, SUM and AVERAGE. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. #R##N#In the last decade, many different approaches have been proposed, with different trade-offs in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of aggregation algorithms, it can be difficult and time consuming to determine which techniques will be more appropriate to use in specific settings, justifying the existence of a survey to aid in this task. #R##N#This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally defines the concept of aggregation, characterizing the different types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.

Includes members:
  Member "spectra robust estimation of distribution functions in networks":
    also connected through other hyperedges:
      (none)
  Member "fault tolerant aggregation flow updating meets mass distribution":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "counting in practical anonymous dynamic networks is polynomial")
  Member "dependability in aggregation by averaging":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spectra robust estimation of distribution functions in networks")
  Member "a survey of green networking research":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy efficient mechanism for smart communication in cellular networks")
  Member "geographic gossip efficient averaging for sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "quantifying differential privacy of gossip protocols in general networks")
  Member "dynamic approaches to in network aggregation":
    also connected through other hyperedges:
      (none)
  Member "geographic gossip efficient aggregation for sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "network coding for computing cut set bounds")
  Member "fast distributed algorithms for computing separable functions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed voting in beep model")

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)