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: "budget constrained execution of multiple bag of tasks applications on the cloud"
  Abstract: Optimising the execution of Bag-of-Tasks (BoT) applications on the cloud is a hard problem due to the trade-offs between performance and monetary cost. The problem can be further complicated when multiple BoT applications need to be executed. In this paper, we propose and implement a heuristic algorithm that schedules tasks of multiple applications onto different cloud virtual machines in order to maximise performance while satisfying a given budget constraint. Current approaches are limited in task scheduling since they place a limit on the number of cloud resources that can be employed by the applications. However, in the proposed algorithm there are no such limits, and in comparison with other approaches, the algorithm on average achieves an improved performance of 10%. The experimental results also highlight that the algorithm yields consistent performance even with low budget constraints which cannot be achieved by competing approaches.

Connected through hyperedge HE-1 (induced by source paper "dyverse dynamic vertical scaling in multi tenant edge environments"):
  with members:
    - "performance estimation of container based cloud to fog offloading"
    - "feasibility of fog computing"
    - "defog fog computing benchmarks"
    - "realizing edge marketplaces challenges and opportunities"
    - "a survey on mobile edge computing the communication perspective"
    - "enorm a framework for edge node resource management"
    - "joint subcarrier and cpu time allocation for mobile edge computing"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"

Connected through hyperedge HE-2 (induced by source paper "a survey and taxonomy of resource optimisation for executing bag of task applications on public clouds"):
  with members:
    - "optex a deadline aware cost optimization model for spark"
    - "managing deadline constrained bag of tasks jobs on hybrid clouds"
    - "executing bag of distributed tasks on virtually unlimited cloud resources"
    - "task scheduling on the cloud with hard constraints"
    - "executing bag of distributed tasks on the cloud investigating the trade offs between performance and cost"
    - "patterns in the chaos a study of performance variation and predictability in public iaas clouds"
    - "cloud benchmarking for performance"

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)