A performance study of monitoring and information services for distributed systems

TLDR

Monitoring and information services are essential components of distributed systems, and quantitative studies help understand performance limits, guide deployment, and evaluate future development. The study aims to evaluate the performance of three monitoring services—MDS2, R‑GMA, and Hawkeye—across distributed systems. The authors conducted scalability experiments varying users, resources, and data volume to assess the services. The experiments revealed that each service behaves differently, with caching or pre‑fetching providing a strong advantage and primary components needing well‑connected sites due to high load.

Abstract

Monitoring and information services form a key component of a distributed system, or Grid. A quantitative study of such services can aid in understanding the performance limitations, advise in the deployment of the monitoring system, and help evaluate future development work. To this end, we study the performance of three monitoring and information services for distributed systems: the Globus Toolkit/spl reg/ Monitoring and Discovery Service (MDS2), the European Data Grid Relational Grid Monitoring Architecture (R-GMA) and Hawkeye, part of the Condor project. We perform experiments to test their scalability with respect to number of users, number of resources and amount of data collected. Our study shows that each approach has different behaviors, often due to their different design goals. In the four sets of experiments we conducted to evaluate the performance of the service components under different circumstances, we found a strong advantage to caching or pre-fetching the data, as well as the need to have primary components at well-connected sites because of the high load seen by all systems.