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: "adaptive dispatching of tasks in the cloud"
  Abstract: The increasingly wide application of Cloud Computing enables the consolidation of tens of thousands of applications in shared infrastructures. Thus, meeting the quality of service requirements of so many diverse applications in such shared resource environments has become a real challenge, especially since the characteristics and workload of applications differ widely and may change over time. This paper presents an experimental system that can exploit a variety of online quality of service aware adaptive task allocation schemes, and three such schemes are designed and compared. These are a measurement driven algorithm that uses reinforcement learning, secondly a "sensible" allocation algorithm that assigns jobs to sub-systems that are observed to provide a lower response time, and then an algorithm that splits the job arrival stream into sub-streams at rates computed from the hosts' processing capabilities. All of these schemes are compared via measurements among themselves and with a simple round-robin scheduler, on two experimental test-beds with homogeneous and heterogeneous hosts having different processing capacities.

Connected through hyperedge HE-1 (induced by source paper "accurate and energy efficient classification with spiking random neural network corrected and expanded version"):
  with members:
    - "deep learning in spiking neural networks"
    - "mask r cnn"
    - "towards a cognitive routing engine for software defined networks"
    - "hyperface a deep multi task learning framework for face detection landmark localization pose estimation and gender recognition"
    - "an end to end trainable neural network for image based sequence recognition and its application to scene text recognition"
    - "you only look once unified real time object detection"
    - "deep speech 2 end to end speech recognition in english and mandarin"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-2 (induced by source paper "a random access g network stability stable throughput and queueing analysis"):
  with members:
    - "performance analysis of a cooperative wireless network with adaptive relays"
    - "stable throughput region of the two user interference channel"
    - "network level cooperation in random access iot networks with aggregators"
    - "optimal energy distribution with energy packet networks"
    - "stable throughput and delay analysis of a random access network with queue aware transmission"
    - "towards a cognitive routing engine for software defined networks"
    - "effect of energy harvesting on stable throughput in cooperative relay systems"
    - "relay assisted multiple access with full duplex multi packet reception"

Connected through hyperedge HE-3 (induced by source paper "deep learning with the random neural network and its applications"):
  with members:
    - "deep learning in multi layer architectures of dense nuclei"
    - "a new learning method for inference accuracy core occupation and performance co optimization on truenorth chip"
    - "convolutional networks for fast energy efficient neuromorphic computing"
    - "unsupervised representation learning with deep convolutional generative adversarial networks"
    - "deep residual learning for image recognition"
    - "striving for simplicity the all convolutional net"
    - "matconvnet convolutional neural networks for matlab"

Connected through hyperedge HE-4 (induced by source paper "optimal energy distribution with energy packet networks"):
  with members:
    - "self sustainability of energy harvesting systems concept analysis and design"
    - "energy harvesting wireless communications a review of recent advances"
    - "transmission with energy harvesting nodes in fading wireless channels optimal policies"
    - "optimal packet scheduling in an energy harvesting communication system"

Connected through hyperedge HE-5 (induced by source paper "a manifesto for future generation cloud computing research directions for the next decade"):
  with members:
    - "cloud benchmarking for maximising performance of scientific applications"
    - "hpc cloud for scientific and business applications taxonomy vision and research challenges"
    - "in datacenter performance analysis of a tensor processing unit"
    - "knowledge infused and consistent complex event processing over real time and persistent streams"
    - "enorm a framework for edge node resource management"
    - "serverless computing current trends and open problems"
    - "demystifying fog computing characterizing architectures applications and abstractions"
    - "snafu function as a service faas runtime design and implementation"

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)