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 "on exploiting transaction concurrency to speed up blockchains"):
  Abstract: Consensus protocols are currently the bottlenecks that prevent blockchain systems from scaling. However, we argue that transaction execution is also important to the performance and security of blockchains. In other words, there are ample opportunities to speed up and further secure blockchains by reducing the cost of transaction execution. #R##N#Our goal is to understand how much we can speed up blockchains by exploiting transaction concurrency available in blockchain workloads. To this end, we first analyze historical data of seven major public blockchains, namely Bitcoin, Bitcoin Cash, Litecoin, Dogecoin, Ethereum, Ethereum Classic, and Zilliqa. We consider two metrics for concurrency, namely the single-transaction conflict rate per block, and the group conflict rate per block. We find that there is more concurrency in UTXO-based blockchains than in account-based ones, although the amount of concurrency in the former is lower than expected. Another interesting finding is that some blockchains with larger blocks have more concurrency than blockchains with smaller blocks. Next, we propose an analytical model for estimating the transaction execution speed-up given an amount of concurrency. Using results from our empirical analysis, the model estimates that 6x speed-ups in Ethereum can be achieved if all available concurrency is exploited.

Includes members:
  Member "blockchains and distributed databases a twin study":
    also connected through other hyperedges:
      (none)
  Member "the security reference architecture for blockchains towards a standardized model for studying vulnerabilities threats and defenses":
    also connected through other hyperedges:
      (none)
  Member "an empirical study of speculative concurrency in ethereum smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dipetrans a framework for distributed parallel execution of transactions of blocks in blockchain")
  Member "hotstuff bft consensus in the lens of blockchain":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "a concurrent perspective on smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an overview on smart contracts challenges advances and platforms")
  Member "adding concurrency to smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an overview on smart contracts challenges advances and platforms")
  Member "blockbench a framework for analyzing private blockchains":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "effective scaling of blockchain beyond consensus innovations and moore s law")
  Member "untangling blockchain a data processing view of blockchain systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "effective scaling of blockchain beyond consensus innovations and moore s law")

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)