  In this paper, we analyze the performance of random load resampling and
migration strategies in parallel server systems. Clients initially attach to an
arbitrary server, but may switch server independently at random instants of
time in an attempt to improve their service rate. This approach to load
balancing contrasts with traditional approaches where clients make smart server
selections upon arrival (e.g., Join-the-Shortest-Queue policy and variants
thereof). Load resampling is particularly relevant in scenarios where clients
cannot predict the load of a server before being actually attached to it. An
important example is in wireless spectrum sharing where clients try to share a
set of frequency bands in a distributed manner.
