Libra: An Economy driven Job Scheduling System for Clusters

TL;DR

Libra is a novel economy-driven cluster scheduler that allocates resources based on user-defined utility, budget, and deadlines, improving user satisfaction and system utility over traditional system-centric schedulers.

Contribution

Introduces Libra, a market-based, economy-driven scheduling system for clusters that supports QoS-based resource allocation as an add-on to existing systems.

Findings

Libra improves user satisfaction compared to traditional schedulers.

The scheduler ensures deadline and budget constraints within O(n) runtime.

Simulation results demonstrate enhanced system utility and user satisfaction.

Abstract

Clusters of computers have emerged as mainstream parallel and distributed platforms for high-performance, high-throughput and high-availability computing. To enable effective resource management on clusters, numerous cluster managements systems and schedulers have been designed. However, their focus has essentially been on maximizing CPU performance, but not on improving the value of utility delivered to the user and quality of services. This paper presents a new computational economy driven scheduling system called Libra, which has been designed to support allocation of resources based on the users? quality of service (QoS) requirements. It is intended to work as an add-on to the existing queuing and resource management system. The first version has been implemented as a plugin scheduler to the PBS (Portable Batch System) system. The scheduler offers market-based economy driven service for managing batch jobs on clusters by scheduling CPU time according to user utility as determined by their budget and deadline rather than system performance considerations. The Libra scheduler ensures that both these constraints are met within an O(n) run-time. The Libra scheduler has been simulated using the GridSim toolkit to carry out a detailed performance analysis. Results show that the deadline and budget based proportional resource allocation strategy improves the utility of the system and user satisfaction as compared to system-centric scheduling strategies.