Representing Job Scheduling for Volunteer Grid Environment using Online Container Stowage
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 12
Abstract
Volunteer grid computing comprises of volunteer resources which are unpredictable in nature and as such the scheduling of jobs among these resources could be very uncer-tain. It is also difficult to ensure the successful completion of submitted jobs on volunteer resources as these resources may opt to withdraw from the grid system anytime or there might be a resource failure, which requires job reassignments. However, a careful consideration of future jobs can make scheduling of jobs more reliable on volunteer resources. There are two possibilities; either to forecast the future jobs or to forecast the resource availability by studying the history events. In this paper an attempt has been made to utilize the future job forecasting in improving the job scheduling experience with volunteer grid resources. A scheduling approach is proposed that uses container stowage to allocate the volunteer grid resources based on the jobs submitted. The proposed scheduling approach optimizes the number of resources actively used. The approach presents online container stowage adaptability for scheduling jobs using volun-teer grid resources. The performance has been evaluated by making comparison to other scheduling algorithms adopted in volunteer grid. The simulation results have shown that the pro-posed approach performs better in terms of average turnaround and waiting time in comparison with existing scheduling algo-rithms. The job load forecast also reduced the number of job reassignments.
Authors and Affiliations
Saddaf Rubab, Mohd Fadzil Hassan, Ahmad Kamil Mahmood, Syed Nasir Mehmood Shah
Keywords
Related Articles
- EP ID EP397358
- DOI 10.14569/IJACSA.2016.071244
- Views 81
- Downloads 0
An Ensemble of Fine-Tuned Heterogeneous Bayesian Classifiers
Bayesian network (BN) classifiers use different structures and different training parameters which leads to diversity in classification decisions. This work empirically shows that building an ensemble of several fine-tun...
Variational Formulation of the Template-Based Quasi-Conformal Shape-from-Motion from Laparoscopic Images
One of the current limits of laparosurgery is the absence of a 3D sensing facility for standard monocular laparoscopes. Significant progress has been made to acquire 3D from a single camera using Visual SLAM (Simultaneou...
Containing a Confused Deputy on x86: A Survey of Privilege Escalation Mitigation Techniques
The weak separation between user- and kernelspace in modern operating systems facilitates several forms of privilege escalation. This paper provides a survey of protection techniques, both cutting-edge and time-tested, u...
Bio-Inspired Clustering of Complex Products Structure based on DSM
Clustering plays an important role in the decomposition of complex products structure. Different clustering algorithms may achieve different effects of the decomposition. This paper aims to proposes a bio-inspired geneti...
Memetic Multi-Objective Particle Swarm Optimization-Based Energy-Aware Virtual Network Embedding
In cloud infrastructure, accommodating multiple virtual networks on a single physical network reduces power consumed by physical resources and minimizes cost of operating cloud data centers. However, mapping multiple vir...