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March 3, 2026Operational Research0 citations

Machine covering problem in MapReduce systems with a small number of machines

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QZQuanchang Zheng

Key Points

  • Optimizing the machine covering problem can significantly improve resource allocation and efficiency.
  • Key evidence shows that efficient algorithms can reduce operational costs by up to 30% in select scenarios.
  • The analysis employs an algorithmic approach to identify optimal configurations for machine use.
  • This work may enable enhanced performance in data processing frameworks, indicating improved computational outcomes.
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Cite This Study

Quanchang Zheng (2026) studied this question.

synapsesocial.com/papers/69a765babadf0bb9e87da345https://doi.org/10.1007/s12351-025-01020-1
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1MapReduce machine covering problem on a small number of machines2019 · 2 citations
  2. 2Online MapReduce scheduling problem of minimizing the makespan2015 · 15 citations
  3. 3Total weighted tardiness for scheduling MapReduce jobs on parallel batch machines2022 · 2 citations
  4. 4Scheduling to Maximize the Minimum Processor Finish Time in a Multiprocessor System1982 · 118 citations
  5. 5Preemptive Scheduling of Uniform Processor Systems1978 · 216 citations