Iterated shared memory models

TL;DR: This talk surveys results in the iterated model with more powerful base tasks or enriched with failure detectors, which have been useful to prove impossibility results and to design algorithms, due to the elegant recursive structure of the runs.

Abstract: In centralized computing we can compute a function composing a sequence of elementary functions, where the output of the i-th function in the sequence is the input to the i+1-st function in the sequence. This computation is done without persistent registers that could store information of the outcomes of these function invocations. In distributed computing, a task is the analogue of a function. An iterated model is defined by some base set of tasks. Processes invoke a sequence of tasks from this set. Each process invokes the i+1-st task with its output from the i-th task. Processes access the sequence of tasks, one-by-one, in the same order, and asynchronously. Any number of processes can crash. In the most basic iterated model the base tasks are read/write registers. Previous papers have studied this and other iterated models with more powerful base tasks or enriched with failure detectors, which have been useful to prove impossibility results and to design algorithms, due to the elegant recursive structure of the runs. This talk surveys results in this area, contributed mainly by Borowsky, Gafni, Herlihy, Raynal, Travers and the author.