Speed is as powerful as clairvoyance
Journal of the ACM (JACM)
Convex quadratic and semidefinite programming relaxations in scheduling
Journal of the ACM (JACM)
A polynomial time approximation scheme for the two-stage multiprocessor flow shop problem
Theoretical Computer Science
Implementation of a PTAS for Scheduling with Release Dates
ALENEX '01 Revised Papers from the Third International Workshop on Algorithm Engineering and Experimentation
Approximability of flow shop scheduling
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Approximation Schemes for Minimizing Average Weighted Completion Time with Release Dates
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Multi-processor scheduling to minimize flow time with ε resource augmentation
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Approximating total flow time on parallel machines
Journal of Computer and System Sciences
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Minimizing Average Flow-time: Upper and Lower Bounds
FOCS '07 Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science
On distributing symmetric streaming computations
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Online scheduling to minimize the maximum delay factor
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Minimizing Total Flow-Time: The Unrelated Case
ISAAC '08 Proceedings of the 19th International Symposium on Algorithms and Computation
Proceedings of the forty-first annual ACM symposium on Theory of computing
MapReduce optimization using regulated dynamic prioritization
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Quincy: fair scheduling for distributed computing clusters
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
Delay scheduling: a simple technique for achieving locality and fairness in cluster scheduling
Proceedings of the 5th European conference on Computer systems
Proceedings of the 19th international conference on World wide web
Assigning tasks for efficiency in Hadoop: extended abstract
Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures
Data-Intensive Text Processing with MapReduce
Data-Intensive Text Processing with MapReduce
Improving MapReduce performance in heterogeneous environments
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
A model of computation for MapReduce
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Better scalable algorithms for broadcast scheduling
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
Algorithms and theory of computation handbook
FLEX: a slot allocation scheduling optimizer for MapReduce workloads
Proceedings of the ACM/IFIP/USENIX 11th International Conference on Middleware
An online scalable algorithm for minimizing lk-norms of weighted flow time on unrelated machines
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
MROrder: flexible job ordering optimization for online mapreduce workloads
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
Joint optimization of overlapping phases in MapReduce
Performance Evaluation
Speeding-up codon analysis on the cloud with local MapReduce aggregation
Information Sciences: an International Journal
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The map-reduce paradigm is now standard in industry and academia for processing large-scale data. In this work, we formalize job scheduling in map-reduce as a novel generalization of the two-stage classical flexible flow shop (FFS) problem: instead of a single task at each stage, a job now consists of a set of tasks per stage. For this generalization, we consider the problem of minimizing the total flowtime and give an efficient 12-approximation in the offline setting and an online (1+µ)-speed O(1/µ2)-competitive algorithm. Motivated by map-reduce, we revisit the two-stage flow shop problem, where we give a dynamic program for minimizing the total flowtime when all jobs arrive at the same time. If there are fixed number of job-types the dynamic program yields a PTAS; it is also a QPTAS when the processing times of jobs are polynomially bounded. This gives the first improvement in approximation of flowtime for the two-stage flow shop problem since the trivial 2-approximation algorithm of Gonzalez and Sahni [29] in 1978, and the first known approximation for the FFS problem. We then consider the generalization of the two-stage FFS problem to the unrelated machines case, where we give an offline 6-approximation and an online (1+µ)-speed O(1/µ4)-competitive algorithm.