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: "multiqueues simpler faster and better relaxed concurrent priority queues"
  Abstract: AbstractPriority queues with parallel access are an attractive data structure for ap-plications like prioritized online scheduling, discrete event simulation, or branch-and-bound. However, a classical priority queue constitutes a severe bottleneck inthis context, leading to very small throughput. Hence, there has been signi cantinterest in concurrent priority queues with a somewhat relaxed semantics wheredeleted elements only need to be close to the minimum. In this paper we presenta very simple approach based on multiple sequential priority queues. It turns outto outperform previous more complicated data structures while at the same timeimproving the quality of the returned elements. 1 Introduction Priority queues are a fundamental data structure with many applications. Priority queuesmanage a set of elements and support the operations for inserting elements and deletingthe smallest element (deleteMin). Whenever we have to dynamically reorder operationsperformed by an algorithm, priority queues can turn out to be useful. Examples includegraph algorithms for shortest paths and minimum spanning trees, discrete event simu-lation, best rst branch-and-bound, and other best rst heuristics. In particular, manysuccessful job scheduling algorithms are of that type. The latter application was the start-ing point for this work focusing on scheduling of jobs with priorities in data managementsystems to support quality of service guarantees (Service Level Agreements).On modern parallel hardware, we often have the situation that p parallel threads(or PEs for processing elements) want to access the priority queue concurrently. This

Connected through hyperedge HE-1 (induced by source paper "fast concurrent data sketches"):
  with members:
    - "distributionally linearizable data structures"
    - "sketching linear classifiers over data streams"
    - "all distances sketches revisited hip estimators for massive graphs analysis"
    - "linearizable implementations do not suffice for randomized distributed computation"

Connected through hyperedge HE-2 (induced by source paper "the lock free k lsm relaxed priority queue"):
  with members:
    - "the adaptive priority queue with elimination and combining"
    - "data structures for task based priority scheduling"

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.DS(Data Structures and Algorithms)