Dynamic Job Scheduling on the Grid Environment using the Great Deluge Algorithm

The utilization of the computational Grid processor network has become a common method for researchers and scientists without access to local processor clusters to avail of the benefits of parallel processing for compute-intensive applications. As a result, this demand requires effective and efficient dynamic allocation of available resources. Although static scheduling and allocation techniques have proved effective, the dynamic nature of the Grid requires innovative techniques for reacting to change and maintaining stability for users. The dynamic scheduling process requires quite powerful optimization techniques, which can themselves lack the performance required in reaction time for achieving an effective schedule solution. Often there is a trade-off between solution quality and speed in achieving a solution. This paper presents an extension of a technique used in optimization and scheduling which can provide the means of achieving this balance and improves on similar approaches currently published.

Job Search Methods and Outcomes

Using Portuguese data, this paper investigates the effects of job search methods on escape rates from unemployment and of job-finding methods on earnings. The effectiveness of the job search process is also evaluated in terms of the periodicity of the resulting job match. Emphasis is accorded the role of the public employment service. Despite its frequency as a search vehicle, the state employment agency is shown to have a low hit rate, and to lead to lower-paying, shorter-lasting jobs.