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• W2345667054 abstract "In this dissertation, we propose Management Architecture for Resource Services (MARS) to address resource management of, and scheduling workflow application onto, a heterogeneous grid. Scheduling in a heterogeneous grid is relatively new area and very few workflow schedulers exist for the grid. In most of the cases, the scheduling process is opportunistic rather than planned, i.e. a waiting task will be executed if a matching workstation is available. This essentially reduces the scheduling process to a much simpler matching routine, leaving complex objective functions such as minimizing response time of the job or optimizing resource utilization outside the picture. In MARS, matching process helps the scheduler, Priority Scheduling in MARS (PRISM), by identifying appropriate resources for executing the task. It is the job of scheduler to map the tasks onto these matching workstations and schedule them for execution. In the scheduling process, PRISM uses backfilling technique to generate the best response time for the job. MARS ability to schedule future jobs also makes backfilling an integral part of the overall scheduling process. The response time of a job includes the time spent by the job in the arrival queue waiting to be scheduled. If the scheduler spends too much time deciding the schedule, the wait time may overshadow the scheduler efforts. Producing the best schedule requires the scheduling algorithms to inspect all the matching workstations. As the number of matching workstations increases the performance of the scheduling algorithm deteriorates, increasing the job scheduling time. PRISM increases the efficiency of the scheduling process by reducing the number of matched resources. This reduction is achieved through careful selection and use of simulated annealing meta-heuristic. To decrease the time complexity further, tabu search is used along with simulated annealing. Reducing the number of matching workstations speeds up the scheduling process and produces acceptable results under normal circumstances. There are, however, cases where meta-heuristics fail to identify the appropriate set of matching workstations. This results in inferior quality schedule. To guide the scheduling algorithm towards the right set of matching workstations, the scheduler is complemented with a feedback phase. The feedback mechanism identifies an inferior schedule and forces the scheduler to increase the number of matching workstations it is evaluating. The scheduler continues to expand the matching workstation set until the schedule improves or all the matching workstations are evaluated. The computational grids, just like data centers, consume a lot of power. This consumption could be direct, such as electricity intake by the workstations, or indirect, such as power consumed by the cooling techniques employed to negate the heat dissipation from the components. The power consumption has become a dominant operational cost for computational grids. The response time of a job depends directly on the number of workstation used to execute the job. Keeping more workstations online would consume more power. In order to outline possible savings in power consumption, MARS include power-aware scheduling which models the scheduling of jobs as a multi-objective problem. The power-aware scheduling algorithm produces different schedules, each with associated cost and response time. The grid manager then selects the schedule which conforms to the high-level policies governing the grid operations. MARS is a unified grid management architecture which includes resource management and job scheduling algorithms. Although the focus of our work is efficient grid scheduling algorithms, MARS also includes provisions for fault-tolerance, task migration and schedule re-evaluation. These are future avenues we would like to explore in MARS project. (Abstract shortened by UMI.)" @default.
• W2345667054 created "2016-06-24" @default.
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• W2345667054 date "2007-01-01" @default.
• W2345667054 modified "2023-09-24" @default.
• W2345667054 title "Grid management architecture for efficient and scalable scheduling of workflow applications" @default.
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