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: "causal consistency beyond memory"
  Abstract: In distributed systems where strong consistency is costly when not impossible, causal consistency provides a valuable abstraction to represent program executions as partial orders. In addition to the sequential program order of each computing entity, causal order also contains the semantic links between the events that affect the shared objects -- messages emission and reception in a communication channel, reads and writes on a shared register. Usual approaches based on semantic links are very difficult to adapt to other data types such as queues or counters because they require a specific analysis of causal dependencies for each data type. This paper presents a new approach to define causal consistency for any abstract data type based on sequential specifications. It explores, formalizes and studies the differences between three variations of causal consistency and highlights them in the light of PRAM, eventual consistency and sequential consistency: weak causal consistency, that captures the notion of causality preservation when focusing on convergence; causal convergence that mixes weak causal consistency and convergence; and causal consistency, that coincides with causal memory when applied to shared memory.

Connected through hyperedge HE-1 (induced by source paper "robustness against transactional causal consistency"):
  with members:
    - "on verifying causal consistency"
    - "robustness against power is pspace complete"
    - "herding cats modelling simulation testing and data mining for weak memory"

Connected through hyperedge HE-2 (induced by source paper "blockchain abstract data type"):
  with members:
    - "formalizing and implementing distributed ledger objects"
    - "hyperledger fabric a distributed operating system for permissioned blockchains"
    - "leader randomization signature free byzantine consensus for consortium blockchains"
    - "monotonic prefix consistency in distributed systems"
    - "enhancing bitcoin security and performance with strong consistency via collective signing"
    - "the weakest failure detector for eventual consistency"
    - "bitcoin meets strong consistency"

Connected through hyperedge HE-3 (induced by source paper "extending causal consistency to any object defined by a sequential specification"):
  with members:
    - "a fault tolerant sequentially consistent dsm with a compositional correctness proof"

Connected through hyperedge HE-4 (induced by source paper "vcube ps a causal broadcast topic based publish subscribe system"):
  with members:
    - "local variation of hashtag spike trains and popularity in twitter"

Connected through hyperedge HE-5 (induced by source paper "on verifying causal consistency"):
  with members:
    - "on reducing linearizability to state reachability"
    - "on the complexity of linearizability"
    - "verifying pram consistency over read write traces of data replicas"

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)