Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving ta...

In an Internet desktop grid, the computing power may be leveraged by providing economic incentive for computer owners. Using batch mode scheduling heuristics, such as MinMin, MaxMin or Sufferage, this paper describes an algorithm that performs independent task scheduling on a large scale heterogeneous system, with a budget constraint. Under the restriction of never exceeding a periodically refr...

Data-intensive Grid applications need access to large data sets that may each be replicated on different resources. Minimizing the overhead of transferring these data sets to the resources where the applications are executed requires that appropriate computational and data resources be selected. In this paper, we consider the problem of scheduling an application composed of a set of independent...

Scheduling is an important factor for the efficient execution of computational workflows on Grid environments. A large number of static scheduling heuristics has been presented in the literature. These algorithms allocate tasks before job execution starts and assume a precise knowledge of timing information, which may be difficult to obtain in general. To overcome this limitation of static stra...

Load balancing is a very important and complex problem in computational grids. A computational grid differs from traditional high performance computing systems in the heterogeneity of the computing nodes and communication links, as well as background workloads that may be present in the computing nodes. There is a need to develop algorithms that could capture this complexity yet can be easily i...

In virtualized systems, allocation and scheduling of resources shared among multiple virtual machines faces challenges such as autonomy, isolation and high workload dynamics. The multiplexing and consolidation nature of virtualized systems also raise issues such as interference and conflicts among various virtual machine instances. Therefore traditional resource allocation strategy can’t achiev...

The need for calculating actions has been emerged everywhere and in any time, by advancing of information technology. Cloud computing is the latest response to such needs. Prominent popularity has recently been created for Cloud computing systems. Increasing cloud efficiency is an important subject of consideration. Heterogeneity and diversity among different resources and requests of users in ...

The need for calculating actions has been emerged everywhere and in any time, by advancing of information technology. Cloud computing is the latest response to such needs. Prominent popularity has recently been created for Cloud computing systems. Increasing cloud efficiency is an important subject of consideration. Heterogeneity and diversity among different resources and requests of users in ...

Cloud computing refers to services that run in a distributed network and are accessible through common internet protocols. It merges a lot of physical resources and offers them to users as services according to service level agreement. Therefore, resource management alongside with task scheduling has direct influence on cloud networks’ performance and efficiency. Presenting a proper scheduling ...

Grid is the system which provides a new, powerful and innovative platform that caters the need of massively computational or data intensive applications from its pool of resources like processors, memory, data, services etc. It differs from traditional computing systems because of its heterogeneous nature and back ground workloads. Performance and utilization of the grid rests on the optimal ba...