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 "allocation of graph jobs in geo distributed cloud networks"):
  Abstract: Recently, processing of big-data has drawn tremendous attention, where cloud computing is a natural platform. Big-data tasks can be represented as a graph job consisting of multiple sub-jobs, which must be executed in parallel with predefined communication constraints. This work develops the foundation for allocating graph jobs in geo-distributed cloud networks (GCs) with various scales. The problem of graph job allocation in GCs is formulated with respect to the incurred power consumption of the tasks, which turns out to be an integer programming problem. Considering the intractability of the solution, a sub-optimal analytical approach, suitable for small-scale GCs, is proposed. Further, in medium scale GDCNs, we address the graph-job allocation problem using a distributed algorithm. Finally, for large-scale GCs, given the intractability of the feasible set of allocations, we propose a novel algorithm called cloud crawling, which consists of a decentralized crawler exploring the network to determine the "potentially good" feasible allocations for the graph jobs. Based on the suggested strategies of the cloud crawler, we address the problem of graph job allocation from the proxy agents' perspective eliminating the burden of job allocation from the cloud datacenters (DCs). We address this problem under robust and adaptive pricing of the DCs, for each of which we propose an effective online learning algorithm.

Includes members:
  Member "a two stage auction mechanism for cloud resource allocation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "power aware allocation of graph jobs in geo distributed cloud networks")
  Member "scheduling storms and streams in the cloud":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "allocation of computation intensive graph jobs over vehicular clouds in iov")

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)