The algorithms described above are all centralized or semicentralized. Distributed algorithms also exist. Typical of these are the ones described by Eager et al. (1986). As mentioned above, in the most cost-effective algorithm they studied, when a process is created, the machine on which it originates sends probe messages to a randomly-chosen machine, asking if its load is below some threshold value. If so, the process is sent there. If not, another machine is chosen for probing. Probing does not go on forever. If no suitable host is found within N probes, the algorithm terminates and the process runs on the originating machine.

An analytical queueing model of this algorithm has been constructed and investigated. Using this model, it was established that the algorithm behaves well and is stable under a wide range of parameters, including different threshold values, transfer costs, and probe limits.

Nevertheless, it should be observed that under conditions of heavy load, all machines will constantly send probes to other machines in a futile attempt to find one that is willing to accept more work. Few processes will be off-loaded, but considerable overhead may be incurred in the attempt to do so.