  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 systems, 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's Monitoring and Discovery Service (MDS), 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 prefetching the data,
as well as the need to have primary components at well connected sites due to
high load seen by all systems.
