In this journal, we proposed a novel method of using multi-task learning to switch the scheduling algorithm. With change algorithm inside framework, framework can create scheduler with best task execution optimization under computation deadline. changing number tasks, types resources taken, and deadline, it is hard for single achieve while avoiding worst-case time complexity in resource-constra...

Scheduling a set of tasks on a set of machines so as to yield an efficient schedule is a basic problem in computer science and operations research. Most of the research on this problem incorporates the potentially unrealistic assumption that communication between the different machines is instantaneous. In this paper we remove this assumption and study the problem of network scheduling, where e...

An Early Quantum Task (EQT) is a Quantum EDF task that has shrunk its first period into one quantum time slot. Its purpose is to be executed as soon as possible, without causing deadline overflow of other tasks. We will derive the conditions under which an EQT can be admitted and can have an immediate start. The advantage of scheduling EQTs is shown by its use in a buffered multi-media server. ...

A common pattern in the architectures of modern interactive web-services is that of large request fan-outs, where even a single end-user request (task) arriving at an application server triggers tens to thousands of data accesses (sub-tasks) to different stateful backend servers. The overall response time of each task is bottlenecked by the completion time of the slowest sub-task, making such w...

Cloud computing is a newly emerging distributed system which is evolved from Grid computing. Task scheduling is the core research of cloud computing which studies how to allocate the tasks among the physical nodes, so that the tasks can get a balanced allocation or each task’s execution cost decreases to the minimum, or the overall system performance is optimal. Unlike task scheduling based on ...

Managing task scheduling management in cloud computing is an essential part for the landscape of complex procedure tasks based on various resources a proficient and scalable path. The aim this research to dynamically optimize aforesaid issue scheduling. improvises imperfection algorithm by pursue weighted fair queuing model, which significantly effective compared existing method. A model has be...

Consider a task scheduling problem of a given fine grained task graph on distributed-memory parallel machines. In this paper, we report that schedules with small makespan generated by existing task scheduling algorithms do not usually become fast parallel programs on distributed-memory parallel machines. That is caused by no consideration to message packaging. To obtain fast parallel programs u...

The constrained multiagent task scheduling problem is a problem class that describes complex scheduling problems that integrate stochastic task allocation with constraint satisfaction for agents that concurrently execute multiple tasks. The combination of elements from constraint satisfaction, task allocation and resource scheduling produces a challenging class of problems. Unfortunately, exist...

Task scheduling policies can be generally classiied as eager scheduling and lazy scheduling. The former attempts to schedule the tasks whenever there are free processors available, while the latter delays the scheduling of some tasks so as to accommodate more appropriate tasks. In this paper we propose a hybrid policy, called eager scheduling with lazy retry (ESLR). This policy tries to schedul...