An In-depth Benchmarking of Evolutionary and Swarm Intelligence Algorithms for Autoscaling Parameter Sweep Applications on Public Clouds

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Parameter</td><td class="align_center">Value</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left"><i>Population size</i></td><td class="align_center">92</td></tr><tr><td class="align_left"><i>Number of evaluations</i></td><td class="align_center">36800</td></tr><tr><td class="align_left"><i>P</i><sub><i>c</i></sub></td><td class="align_center">1</td></tr><tr><td class="align_left"><i>D</i><sub><i>c</i></sub></td><td class="align_center">30</td></tr><tr><td class="align_left"><i>P</i><sub><i>m</i></sub></td><td class="align_center">1/15</td></tr><tr><td class="align_left"><i>D</i><sub><i>m</i></sub></td><td class="align_center">20</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Parameter setting of SMS-EMOA.</div>

Scientific Programming

tab5

Table 5

Table 5: An In-depth Benchmarking of Evolutionary and Swarm Intelligence Algorithms for Autoscaling Parameter Sweep Applications on Public Clouds 