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.

The determinants of performance appraisal systems: A note (Do Brown and Heywood's results for Australia hold up for Britain?)

This article offers a replication for Britain of Brown and Heywood's analysis of the determinants of performance appraisal in Australia. Although there are some important limiting differences between our two datasets - the Australia Workplace Industrial Relations Survey (AWIRS) and the Workplace Employment Relations Survey (WERS) - we reach one central point of agreement and one intriguing shared insight. First, performance appraisal is negatively associated with tenure: where employers cannot rely on the carrot of deferred pay or the stick of dismissal to motivate workers, they will tend to rely more on monitoring, ceteris paribus. Second, employer monitoring and performance pay may be complementary. However, consonant with the disparate results from the wider literature, there is more modest agreement on the contribution of specific human resource management practices, and still less on the role of job control.

Organizational culture predicts job satisfaction and perceived clinical effectiveness in pediatric primary care practices

Background: In recent years, there has been a growing understanding that organizational culture is related to an organization's performance. However, fewstudies have examined organizational culture in medical group practices. Objectives: The purpose of this study was to examine the relationship of organizational culture on provider job satisfaction and perceived clinical effectiveness in primary care pediatric practices. Research Design: This cross-sectional study included 36 primary care pediatric practices located in Connecticut. Participants: There were 374 participants in this study, which included 127 clinicians and 247 nonclinicians. Measures: Office managers completed a questionnaire that recorded staff and practice characteristics; all participants completed the Organizational Culture Scale, a questionnaire that assessed the practice on four cultural domains (i.e., group, developmental, rational, and hierarchical), and the Primary Care Organizational Questionnaire that evaluated perceived effectiveness and job satisfaction. Results: Hierarchical linear models using a restricted maximum likelihood estimation method were used to evaluate whether the practice culture types predicted job satisfaction and perceived effectiveness. Group culture was positively associated with both satisfaction and perceived effectiveness. In contrast, hierarchical and rational culture were negatively associated with both job satisfaction and perceived effectiveness. These relationships were true for clinicians, nonclinicians, and the practice as a whole. Conclusions: Our study demonstrates that practice culture is associated with job satisfaction and perceived clinical effectiveness and that a group culture was associated with high job satisfaction and perceived effectiveness. Copyright © 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins.

Automating fault tolerance in high-performance computational biological jobs using multi-agent approaches

Background: Large-scale biological jobs on high-performance computing systems require manual intervention if one or more computing cores on which they execute fail. This places not only a cost on the maintenance of the job, but also a cost on the time taken for reinstating the job and the risk of losing data and execution accomplished by the job before it failed. Approaches which can proactively detect computing core failures and take action to relocate the computing core's job onto reliable cores can make a significant step towards automating fault tolerance. Method: This paper describes an experimental investigation into the use of multi-agent approaches for fault tolerance. Two approaches are studied, the first at the job level and the second at the core level. The approaches are investigated for single core failure scenarios that can occur in the execution of parallel reduction algorithms on computer clusters. A third approach is proposed that incorporates multi-agent technology both at the job and core level. Experiments are pursued in the context of genome searching, a popular computational biology application. Result: The key conclusion is that the approaches proposed are feasible for automating fault tolerance in high-performance computing systems with minimal human intervention. In a typical experiment in which the fault tolerance is studied, centralised and decentralised checkpointing approaches on an average add 90% to the actual time for executing the job. On the other hand, in the same experiment the multi-agent approaches add only 10% to the overall execution time