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| Content Provider | ACM Digital Library |
|---|---|
| Author | Chung, Christine Souza, Alexander Nonner, Tim |
| Abstract | We consider the classical problem of scheduling preemptible jobs, that arrive over time, on identical parallel machines. The goal is to minimize the total completion time of the jobs. In standard scheduling notation of Graham et al. [5], this problem is denoted $P|r_{j},$ $pmtn|Σ_{j}/^{cj}.$ A popular algorithm called SRPT, which always schedules the unfinished jobs with shortest remaining processing time, is known to be 2-competitive, see Phillips et al. [13, 14]. This is also the best known competitive ratio for any online algorithm. However, it is conjectured that the competitive ratio of SRPT is significantly less than 2. Even breaking the barrier of 2 is considered a significant step towards the final answer of this classical online problem. We improve on this open problem by showing that SRPT is 1.86-competitive. This result is obtained using the following method, which might be of general interest: We define two dependent random variables that sum up to the difference between the cost of an SRPT schedule and the cost of an optimal schedule. Then we bound the sum of the expected values of these random variables with respect to the cost of the optimal schedule, yielding the claimed competitiveness. Furthermore, we show a lower bound of 21/19 for SRPT, improving on the previously best known 12/11 due to Lu et al. [11]. |
| Starting Page | 1373 |
| Ending Page | 1388 |
| Page Count | 16 |
| File Format | |
| ISBN | 9780898716986 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-01-17 |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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