Latency-based Vector Scheduling of Many-task Applications for a Hybrid Cloud

Abstract

A centralized scheduler can become a bottleneck for placing the tasks of a many-task application on heterogeneous cloud resources. We have previously demonstrated that a de-centralized vector scheduling approach based on performance measurements can be used successfully for this task placement scenario. In this paper, we extend this approach to task placement based on latency measurements. Each node collects the performance measurements from its neighbors on an overlay graph, measures the communication latency, and then makes local decisions on where to move tasks. We present a centralized algorithm for configuring the overlay graph based on latency measurements and extend the vector scheduling approach to take latency into considerations. Our experiments in CloudLab demonstrate that this approach results in better performance and resource utilization than without latency information.