A Feedback Control Mechanism for Balancing I/O- and Memory-Intensive Applications on Clusters

Feedback Control Mechanism for Balancing I / O - Andmemory - Intensive Applications On

Dynamic Load Balancing for I/O- and Memory-Intensive Workload in clusters Using a Feedback Control Mechanism

1 One common assumption of the existing models of load balancing is that the weights of resources and I/O buffer size are statically configured. Though the static configuration of these parameters performs well in a cluster where the workload can be predicted, its performance is poor in dynamic systems where the workload is unknown. In this paper, a new feedback control mechanism is proposed to...

Performance comparisons of load balancing algorithms for I/O-intensive workloads on clusters

Load balancing techniques play a critically important role in developing high-performance cluster computing platforms. Existing load balancing approaches are concerned with the effective usage of CPU and memory resources. Due to imbalance in disk I/O resources under I/O-intensive workloads, the previous CPUor memory-aware load balancing schemes suffer significant performance drop. To remedy thi...

Boosting Performance for I/O-Intensive Workload by Preemptive Job Migrations in a Cluster System

Load balancing in a cluster system has been investigated extensively, mainly focusing on the effective usage of global CPU and memory resources. However, if a significant portion of applications running in the system is I/O-intensive, traditional load balancing policies that focus on CPU and memory usage may cause the system performance to decrease substantially. To solve this problem, a new I/...

Dynamic Load Balancing for I/O-Intensive Tasks on Heterogeneous Clusters

1 Since I/O-intensive tasks running on a heterogeneous cluster need a highly effective usage of global I/O resources, previous CPUor memory-centric load balancing schemes suffer significant performance drop under I/O-intensive workload due to the imbalance of I/O load. To solve this problem, we develop two I/O-aware load-balancing schemes, which consider system heterogeneity and migrate more I/...