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: "a flexible n 2 adversary node resistant and halting recoverable blockchain sharding protocol"
  Abstract: Blockchain sharding is a promising approach to solving the dilemma between decentralisation and high performance (transaction throughput) for blockchain. The main challenge of Blockchain sharding systems is how to reach a decision on a statement among a sub-group (shard) of people while ensuring the whole population recognises this statement. Namely, the challenge is to prevent an adversary who does not have the majority of nodes globally but have the majority of nodes inside a shard. Most Blockchain sharding approaches can only reach a correct consensus inside a shard with at most $n/3$ evil nodes in a $n$ node system. There is a blockchain sharding approach which can prevent an incorrect decision to be reached when the adversary does not have $n/2$ nodes globally. However, the system can be stopped from reaching consensus (become deadlocked) if the adversary controls a smaller number of nodes. #R##N#In this paper, we present an improved Blockchain sharding approach that can withstand $n/2$ adversarial nodes and recover from deadlocks. The recovery is made by dynamically adjusting the number of shards and the shard size. A performance analysis suggests our approach has a high performance (transaction throughput) while requiring little bandwidth for synchronisation.

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)