Online Algorithm Scheduling : The Studies
This time we will see Online Algorithm Scheduling studies from different subtopics.
Achieving Achievable Scheduling With flexible online algorithms
An article about online scheduling with learning on a single machine finds that the real processing time of job J j is an increasing function of its position h. Our flexible online algorithm canPlan the processing time of any number of jobs simultaneously, so it is perfect for future endeavors in the field of online scheduling.
Analizing the Effects of Scheduling Algorithms on the Overall Managed Process
A study about scheduling algorithms was conducted using the objective of understanding their performance and its effects on the overall managed process. The study found that distinct scheduling algorithms can have different strategic effects on the resulting process. The most effective scheduling algorithm is when it makes use of data model and knowledge factors to effectively manage resources.
Sequence-parallelism Scheduling Algorithms: A Comprehensive Guide
A study about online scheduling algorithms is presented. It's found that there are a few methods out there for online scheduling and that the most efficient one is to use a Sequence-parallelism co-ordinator.
Perturbation Affects Job Quality
An analysis about the effects of perturbations on job quality was conducted with the aim to understand how they affect it. It was found that, if job processing times are disturbed and consequently turn out to be longer than the declared ones, the quality of the assignments is affected. In fact, it was found that, depending on the amount of perturbations, some tasks may even be skipped altogether.
The Best Algorithm for Scheduling Use in Online Caching
A research about the optimization of scheduling using online algorithms has found that the best algorithm with a competitive ratio of at most 1.5798 has an advantage for job sizes greater than the machine cost. Additionally, the study found that the optimal algorithm forms a convoy in an L1 network with a competitive ratio of 4/3.
Solving Task Assignment in Cloud Computing Systems with a Scheduler
A study about the scheduler of a cloud computing system is presented. It has been found that the scheduler can be used to solve the problem of task assignment in a cloud computing system. The study found that the scheduler assigned different priorities to tasks according to their dependencies. The scheduler used predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes.
A Preliminary Study of Use of Parallel Machines to rigorously Optimize Workflows
A journal about ordering jobs on parallel machines has been performed. The paper generalizes the analysis of on-line scheduling for uniform machines by considering an algorithm with a competitive ratio of 7.4641. This is better than the best existing result and can be used in practice to optimize release times.
Online and Offline Scheduling Algorithms Differently Realize Conflicting Jobs
A journal about online and offline Scheduling algorithms showed that online algorithms are more accurate than offline algorithms for scheduling conflicting jobs. Online algorithms inserted the conflicting job earlier into the schedule, which caused less conflict.
The Efficiency of Delta-Based Algorithms in Single Machine Scheduling
A research about semi-online algorithms for single machine scheduling with given total processing time shows that a delta-based algorithm is more efficient than a traditional round-robin algorithm. Delta-based algorithms improve the performance when it comes to smoothness and compliance with deadlines.
The Branch and Bound Algorithm for the Project Duration Problem
A research about a constructive branch-and-bound algorithm for the project duration problem with partially renewable resources and general temporal constraints. The study found that a constructive branch-and-bound algorithm is able to solve the problem quickly and accurately.