ﻻ يوجد ملخص باللغة العربية
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 tasks execution cost decreases to the minimum, or the overall system performance is optimal. Unlike task scheduling based on time or cost before, aiming at the special reliability requirements in cloud computing, we propose a non-cooperative game model for reliability-based task scheduling approach. This model takes the steady-state availability that computing nodes provide as the target, takes the task slicing strategy of the schedulers as the game strategy, then finds the Nash equilibrium solution. And also, we design a task scheduling algorithm based on this model. The experiments can be seen that our task scheduling algorithm is better than the so-called balanced scheduling algorithm.
A fundamental problem in distributed computing is the task of cooperatively executing a given set of $t$ tasks by $p$ processors where the communication medium is dynamic and subject to failures. The dynamics of the communication medium lead to group
Internet supercomputing is an approach to solving partitionable, computation-intensive problems by harnessing the power of a vast number of interconnected computers. For the problem of using network supercomputing to perform a large collection of ind
Cloud computing is a newly emerging distributed computing 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 balan
As the quantity and complexity of information processed by software systems increase, large-scale software systems have an increasing requirement for high-performance distributed computing systems. With the acceleration of the Internet in Web 2.0, Cl
This paper studies the problem of distributed beam scheduling for 5G millimeter-Wave (mm-Wave) cellular networks where base stations (BSs) belonging to different operators share the same spectrum without centralized coordination among them. Our goal