Efficient Deep Learning Approach for Computational Offloading in Mobile Edge Computing Networks

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Scheme</td><td class="align_center">Accuracy (%)</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">EDLO</td><td class="align_center">99.67</td></tr><tr><td class="align_left">TEP</td><td class="align_center">62.16</td></tr><tr><td class="align_left">ROS</td><td class="align_center">0.05</td></tr><tr><td class="align_left">DLO</td><td class="align_center">91.23</td></tr><tr><td class="align_left">TEP</td><td class="align_center">38.01</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Wireless Communications and Mobile Computing

tab3

Table 3

Table 3: Efficient Deep Learning Approach for Computational Offloading in Mobile Edge Computing Networks 