Computational and biological systems are often distributed so that processors (cells) jointly solve a task, without any of them receiving all inputs or observing all outputs. Maximal independent set (MIS) selection is a fundamental distributed computing procedure that seeks to elect a set of local leaders in a network. A variant of this problem is solved during the development of the fly's nervous system, when sensory organ precursor (SOP) cells are chosen. By studying SOP selection, we derived a fast algorithm for MIS selection that combines two attractive features. First, processors do not need to know their degree; second, it has an optimal message complexity while only using one-bit messages. Our findings suggest that simple and efficient algorithms can be developed on the basis of biologically derived insights.
An atomic snapshot memory is a shared data structure allowing concurrent processes to store information in a collection of shared registers, all of which may be read in a single atomic scan operation. This paper presents three wait-free implementations of atomic snapshot memory. Two constructions implement wait-free single-writer atomic snapshot memory from wait-free atomic single-writer, n-reader registers. A third construction implements a wait-free n-writer atomic snapshot memory from n-writer, n-reader registers. The first implementation uses unbounded
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