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 and latency optimality friend or foe"
  Abstract: Causal consistency is an attractive consistency model for replicated data stores. It is provably the strongest model that tolerates partitions, it avoids the long latencies associated with strong consistency, and, especially when using read-only transactions, it prevents many of the anomalies of weaker consistency models. Recent work has shown that causal consistency allows "latency-optimal" read-only transactions, that are nonblocking, single-version and single-round in terms of communication. On the surface, this latency optimality is very appealing, as the vast majority of applications are assumed to have read-dominated workloads. #R##N#In this paper, we show that such "latency-optimal" read-only transactions induce an extra overhead on writes, the extra overhead is so high that performance is actually jeopardized, even in read-dominated workloads. We show this result from a practical and a theoretical angle. #R##N#First, we present a protocol that implements "almost laten- cy-optimal" ROTs but does not impose on the writes any of the overhead of latency-optimal protocols. In this protocol, ROTs are nonblocking, one version and can be configured to use either two or one and a half rounds of client-server communication. We experimentally show that this protocol not only provides better throughput, as expected, but also surprisingly better latencies for all but the lowest loads and most read-heavy workloads. #R##N#Then, we prove that the extra overhead imposed on writes by latency-optimal read-only transactions is inherent, i.e., it is not an artifact of the design we consider, and cannot be avoided by any implementation of latency-optimal read-only transactions. We show in particular that this overhead grows linearly with the number of clients.

Connected through hyperedge HE-1 (induced by source paper "distributed transactional systems cannot be fast"):
  with members:
    - "paris causally consistent transactions with non blocking reads and partial replication"
    - "distributed transactional reads the strong the quick the fresh the impossible"
    - "size aware sharding for improving tail latencies in in memory key value stores"
    - "yesquel scalable sql storage for web applications"
    - "a critique of ansi sql isolation levels"

Connected through hyperedge HE-2 (induced by source paper "paris causally consistent transactions with non blocking reads and partial replication"):
  with members:
    - "distributed transactional reads the strong the quick the fresh the impossible"
    - "global stabilization for causally consistent partial replication"
    - "unobtrusive deferred update stabilization for efficient geo replication"

Connected through hyperedge HE-3 (induced by source paper "distributed transactional reads the strong the quick the fresh the impossible"):
  with members:
    - "a critique of ansi sql isolation levels"

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)