A dynamic scheduling benchmark: design, implementation and performance evaluation

TitleA dynamic scheduling benchmark: design, implementation and performance evaluation
Publication TypeConference Paper
Year of Publication1999
AuthorsHamidzadeh, B., and N. Kee
Conference NameTools with Artificial Intelligence, 1999. Proceedings. 11th IEEE International Conference on
Pagination311 -318
Keywordscomputer games, dynamic scheduling benchmark, execution phase, game benchmarks, on-line problem solving techniques, optimization, performance evaluation, performance trade-offs, problem constraints, problem solving, rules, schedule quality, scheduling, scheduling time, semantics, static scheduling techniques, Tetris computer game, video games, workstation clusters, workstation network

Puzzles have traditionally been used as popular benchmarks for evaluating different problem solving strategies. Many of the game benchmarks are suitable for evaluating static scheduling techniques. In such benchmarks, the scheduling phase and the execution phase (i.e. when the schedule is executed to play the game) are disjoint. The scheduling technique can be executed to compute a complete schedule prior to the execution of any moves to play the game. Due to recent interest in on-line problem solving techniques, there is a need for benchmarks which can evaluate the performance trade-offs of dynamic scheduling techniques. Many modern video and computer games can be suitable candidates for dynamic scheduling benchmarks, since they require on-line problem solving. These benchmarks and their system testbeds should be chosen and implemented such that they can accurately reveal important performance trade-offs of dynamic scheduling techniques. In this paper, we introduce a dynamic scheduling benchmark and its system testbed. This benchmark is based on an extended version of the Tetris computer game. The rules and semantics of the game were modified to lend themselves well to evaluation of discrete problem solving and optimization techniques. The system testbed is implemented in a distributed and asynchronous fashion, on a network of workstations, to reveal performance trade-offs between scheduling time, schedule quality, and problem constraints


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