Dynamic scheduling and analysis of real time systems with multiprocessors |
| |
Affiliation: | 1. University of Massachusetts Dartmouth, USA;2. Datang Telecom Technology & Industry Group;3. New Jersey Institute of Technology, USA;4. University of Kentucky, USA |
| |
Abstract: | This research work considers a scenario of cloud computing job-shop scheduling problems. We consider m realtime jobs with various lengths and n machines with different computational speeds and costs. Each job has a deadline to be met, and the profit of processing a packet of a job differs from other jobs. Moreover, considered deadlines are either hard or soft and a penalty is applied if a deadline is missed where the penalty is considered as an exponential function of time. The scheduling problem has been formulated as a mixed integer non-linear programming problem whose objective is to maximize net-profit. The formulated problem is computationally hard and not solvable in deterministic polynomial time. This research work proposes an algorithm named the Tube-tap algorithm as a solution to this scheduling optimization problem. Extensive simulation shows that the proposed algorithm outperforms existing solutions in terms of maximizing net-profit and preserving deadlines. |
| |
Keywords: | Job-shop scheduling problems JSP LPT SPT LS EDD Tube-tap MINLP |
本文献已被 ScienceDirect 等数据库收录! |