  From the era of big science we are back to the "do it yourself", where you do
not have any money to buy clusters or subscribe to grids but still have
algorithms that crave many computing nodes and need them to measure
scalability. Fortunately, this coincides with the era of big data, cloud
computing, and browsers that include JavaScript virtual machines. Those are the
reasons why this paper will focus on two different aspects of volunteer or
freeriding computing: first, the pragmatic: where to find those resources,
which ones can be used, what kind of support you have to give them; and then,
the theoretical: how evolutionary algorithms can be adapted to an environment
in which nodes come and go, have different computing capabilities and operate
in complete asynchrony of each other. We will examine the setup needed to
create a very simple distributed evolutionary algorithm using JavaScript and
then find a model of how users react to it by collecting data from several
experiments featuring different classical benchmark functions.
