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 "dipetrans a framework for distributed parallel execution of transactions of blocks in blockchain"):
  Abstract: In most of the modern day blockchain, transactions are executed serially by both miners and validators; also, PoW is determined serially. The serial execution limits the system throughput and increases transaction acceptance latency, even unable to exploit the modern multi-core resources efficiently. We propose a framework $DiPETrans$ for parallel execution of block transactions. In $DiPETrans$, trusted peers in the blockchain network form a community to execute transactions and to find PoW parallelly. The community follows a master-slave approach for parallel execution. The master analyzes transactions using a static analysis based technique, creates different shards of non-conflicting transactions, and distribute shards to community members for parallel execution. After transaction execution, find PoW parallelly. On successful creation of a block, the master broadcasts proposed block to other peers in the network for validation. On receiving a block, validators re-executes the block transactions, either parallelly (community) or serially (solo validators). If they reach the same state as shared by the miner, then accept the block otherwise reject. We proposed two different approaches for the validator. In first $Sharing\ Validator--$ miner shares the dependency information (shard) in the block to help validators to execute the transaction parallelly, while in another $Default\ Validator--$ no dependency information is shared with validators. We report experiments using 5,170,597 transactions from the Ethereum blockchain and execute them using our $DiPETrans$ framework to empirically validate the benefits of our techniques over traditional sequential execution. We achieved a maximum speedup of $2.18\times$ for the miner, $2.02\times$ for the $Default\ Validator$, and $2.04\times$ for $Sharing\ Validator$ for 100 to 500 transactions per block, when using 6 workers in the community.

Includes members:
  Member "achieving greater concurrency in execution of smart contracts using object semantics":
    also connected through other hyperedges:
      (none)
  Member "security and privacy on blockchain":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the security reference architecture for blockchains towards a standardized model for studying vulnerabilities threats and defenses")
  Member "an empirical study of speculative concurrency in ethereum smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on exploiting transaction concurrency to speed up blockchains")
  Member "a true concurrent model of smart contracts executions":
    also connected through other hyperedges:
      (none)
  Member "an efficient framework for optimistic concurrent execution of smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an overview on smart contracts challenges advances and platforms")
  Member "chainspace a sharded smart contracts platform":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "adding concurrency to smart contracts":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an overview on smart contracts challenges advances and platforms")
  Member "the miner s dilemma":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")

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)