| Résumé | Parallel processing is a way to use resources efficiently by processing
several jobs simultaneously on different servers. In a well controlled environment
where the status of the servers and the jobs are well known, everything is nearly
deterministic and replicating jobs on different servers is wasteful.
However, in a poorly controlled environment where the servers are
unreliable and/or their capacity is highly variable, it is desirable to
design a system that is robust in the sense that it is not affected by the poorly
performing servers. By replicating jobs and assigning them to several
different servers simultaneously, we not only achieve robustness but can
also make the system more efficient under certain conditions so that the
jobs are processed at a faster rate overall. We consider
the option of replicating jobs and study how the performance of different
“degrees” of replication, ranging from no replication to full
replication, affects the performance of a system of parallel servers.
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