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: "on the effect of task to worker assignment in distributed computing systems with stragglers"
  Abstract: We study the expected completion time of some recently proposed algorithms for distributed computing which redundantly assign computing tasks to multiple machines in order to tolerate a certain number of machine failures. We analytically show that not only the amount of redundancy but also the task-to-machine assignments affect the latency in a distributed system. We study systems with a fixed number of computing tasks that are split in possibly overlapping batches, and independent exponentially distributed machine service times. We show that, for such systems, the uniform replication of non- overlapping (disjoint) batches of computing tasks achieves the minimum expected computing time.

Connected through hyperedge HE-1 (induced by source paper "age of information for updates with distortion constant and age dependent distortion constraints"):
  with members:
    - "age of information for computation intensive messages in mobile edge computing"
    - "age of information aware cache updating with file and age dependent update durations"
    - "timely distributed computation with stragglers"
    - "age of information for updates with distortion"
    - "towards the tradeoff between service performance and information freshness"
    - "age of information with finite horizon and partial updates"
    - "online timely status updates with erasures for energy harvesting sensors"
    - "minimizing age of information with soft updates"

Connected through hyperedge HE-2 (induced by source paper "age of information for updates with distortion"):
  with members:
    - "age of information for computation intensive messages in mobile edge computing"
    - "towards the tradeoff between service performance and information freshness"
    - "online timely status updates with erasures for energy harvesting sensors"
    - "minimizing age of information with soft updates"
    - "optimal status updating for an energy harvesting sensor with a noisy channel"
    - "minimizing content staleness in dynamo style replicated storage systems"
    - "coded status updates in an energy harvesting erasure channel"
    - "age minimal online policies for energy harvesting sensors with random battery recharges"

Connected through hyperedge HE-3 (induced by source paper "heterogeneous coded computation across heterogeneous workers"):
  with members:
    - "computation scheduling for distributed machine learning with straggling workers"
    - "hierarchical coded computation"
    - "wireless network intelligence at the edge"
    - "speeding up distributed machine learning using codes"
    - "speeding up distributed gradient descent by utilizing non persistent stragglers"
    - "on the optimal recovery threshold of coded matrix multiplication"
    - "coded computation over heterogeneous clusters"
    - "near optimal straggler mitigation for distributed gradient methods"

Connected through hyperedge HE-4 (induced by source paper "redundancy scheduling in systems with bi modal job service time distribution"):
  with members:
    - "straggler mitigation at scale"
    - "speeding up distributed machine learning using codes"
    - "straggler mitigation by delayed relaunch of tasks"
    - "effective straggler mitigation which clones should attack and when"
    - "efficient redundancy techniques for latency reduction in cloud systems"
    - "on the delay storage trade off in content download from coded distributed storage systems"

Connected through hyperedge HE-5 (induced by source paper "scheduling in the presence of data intensivecompute jobs"):
  with members:
    - "straggler mitigation at scale"
    - "redundancy scheduling in systems with bi modal job service time distribution"
    - "on the delay storage trade off in content download from coded distributed storage systems"

Connected through hyperedge HE-6 (induced by source paper "data replication for reducing computing time in distributed systems with stragglers"):
  with members:
    - "straggler mitigation at scale"
    - "coding for fast content download"

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)