Name
Abstract | ||
|---|---|---|
The availability of a large number of separate clusters has given rise to the field of multicluster systems in which these resources are coupled to obtain their combined benefits to solve large-scale compute-intensive applications. However, it is challenging to achieve automatic load balancing of the jobs across these participating autonomic systems. We developed a novel user space execution model named DA-TC to address the workload allocation techniques for the applications with large number of sequential jobs in multicluster systems. Through this model, we can achieve dynamic load balancing for task assignment, and slower resources become beneficial factors rather than bottlenecks for application execution. The effectiveness of this strategy is demonstrated through theoretical analysis. This model is also evaluated through extensive experimental studies and the results show that when compared with the traditional method, the proposed DA-TC model can significantly improve the performance of application execution in terms of application turnaround time and system reliability in multicluster circumstances. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s10586-012-0228-5 | Cluster Computing |
Keywords | Field | DocType |
Scheduling,Execution management,Load balancing,Cluster computing,Multi-clusters,Distributed systems | Workload,Load balancing (computing),Scheduling (computing),Computer science,Parallel computing,Real-time computing,Turnaround time,Execution model,Dynamic load balancing,User space,Computer cluster,Distributed computing | Journal |
Volume | Issue | ISSN |
17 | 2 | 1386-7857 |
Citations | PageRank | References |
2 | 0.39 | 34 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhifeng Yun | 1 | 91 | 6.95 |
| Zhou Lei | 2 | 17 | 5.15 |
| Gabrielle Allen | 3 | 839 | 116.72 |
| Daniel S. Katz | 4 | 1496 | 121.04 |
| Jagannathan Ramanujam | 5 | 15 | 1.57 |