Process control and scheduling issues for multiprogrammed shared-memory multiprocessors
SOSP '89 Proceedings of the twelfth ACM symposium on Operating systems principles
Theoretical Computer Science - Special issue on dynamic and on-line algorithms
Randomized algorithms
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Speed is as powerful as clairvoyance
Journal of the ACM (JACM)
Broadcast scheduling: when fairness is fine
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Non-clair voy ant multiprocessor scheduling of jobs with changing execution characteristics
Journal of Scheduling - Special issue: On-line scheduling
Handbook on Scheduling: Models and Methods for Advanced Planning (International Handbooks on Information Systems)
Pull-based data broadcast with dependencies: be fair to users, not to items
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Probabilistic computations: Toward a unified measure of complexity
SFCS '77 Proceedings of the 18th Annual Symposium on Foundations of Computer Science
Non-clairvoyant scheduling with precedence constraints
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Scalably scheduling processes with arbitrary speedup curves
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Speed scaling of processes with arbitrary speedup curves on a multiprocessor
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
Scheduling jobs with varying parallelizability to reduce variance
Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures
Minimizing maximum flowtime of jobs with arbitrary parallelizability
WAOA'10 Proceedings of the 8th international conference on Approximation and online algorithms
Speed scaling for energy and performance with instantaneous parallelism
TAPAS'11 Proceedings of the First international ICST conference on Theory and practice of algorithms in (computer) systems
Scalably scheduling processes with arbitrary speedup curves
ACM Transactions on Algorithms (TALG)
Competitive online adaptive scheduling for sets of parallel jobs with fairness and efficiency
Journal of Parallel and Distributed Computing
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In real systems, such as operating systems, the scheduler is often unaware of the remaining work in each job or of the ability of the job to take advantage of more resources. In this paper, we adopt the setting for non-clairvoyance of [3,2]. Based on the particular case of malleable jobs, it is generally assumed in the literature that "Equi never starves a job since it allocates to every job the same amount of processing power". We provide an analysis of the competitiveness of Equi for the makespan objective which shows that under this more general setting this statement is at the same time true and false: false, because, some jobs may be stretched by a factor as large as, but no more than, lnn/ln ln n with respect to the optimal, where n is the size of the largest set; true, because no algorithm can achieve a better competitive ratio up to a constant factor. In this paper, we extend the results in [2,11] to the batch scheduling of sets of jobs that go through arbitrary phases: user request all together at time 0, for the execution of a set of jobs and is served when the last job completes. We prove that the algorithm EquioEqui is (2 + √3 + o(1)) lnn/ln ln n-competitive, where n is the maximum size of a set, which is optimal up to a constant factor. We provide experimental evidences that this algorithm may have the same asymptotic competitive ratio Θ(lnn/ln ln n) (independent of the number of requests) for the flowtime objective when requests have release dates, if it is given sufficiently large extra processing power with respect to the optimum.