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: "blockchain goes green an analysis of blockchain on low power nodes"
  Abstract: Motivated by the massive energy usage of blockchain, on the one hand, and by significant performance improvements in low-power, wimpy systems, on the other hand, we perform an in-depth time-energy analysis of blockchain systems on low-power nodes in comparison to high-performance nodes. We use three low-power systems to represent a wide range of the performance-power spectrum, while covering both x86/64 and ARM architectures. We show that low-end wimpy nodes are struggling to run full-fledged blockchains mainly due to their small and low-bandwidth memory. On the other hand, wimpy systems with balanced performance-to-power ratio achieve reasonable performance while saving significant amounts of energy. For example, Jetson TX2 nodes achieve around 80% and 30% of the throughput of Parity and Hyperledger, respectively, while using 18x and 23x less energy compared to traditional brawny servers with Intel Xeon CPU.

Connected through hyperedge HE-1 (induced by source paper "effective scaling of blockchain beyond consensus innovations and moore s law"):
  with members:
    - "concurrency and privacy with payment channel networks"
    - "scalable byzantine consensus via hardware assisted secret sharing"
    - "an energy efficient reconfigurable dtls cryptographic engine for securing internet of things applications"
    - "morph an adaptive framework for efficient and byzantine fault tolerant sdn control plane"
    - "towards scaling blockchain systems via sharding"
    - "a scale out blockchain for value transfer with spontaneous sharding"
    - "scaling nakamoto consensus to thousands of transactions per second"
    - "blockbench a framework for analyzing private blockchains"

Connected through hyperedge HE-2 (induced by source paper "the disruptions of 5g on data driven technologies and applications"):
  with members:
    - "an e2e simulator for 5g nr networks"
    - "federated machine learning concept and applications"
    - "recommendations with negative feedback via pairwise deep reinforcement learning"
    - "mobilenetv2 inverted residuals and linear bottlenecks"
    - "regularized evolution for image classifier architecture search"
    - "shufflenet v2 practical guidelines for efficient cnn architecture design"
    - "proxylessnas direct neural architecture search on target task and hardware"
    - "towards scaling blockchain systems via sharding"

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)