Cloudlet Selection in Cache-Enabled Fog Networks for Latency Sensitive IoT Applications

Over the coming years, the foresighted enormous increase in smart devices supporting Internet-of-Things (IoT) applications demand novelty in network design. A promising solution to the ever-increasing low-latency requirement of IoT applications is the development of fog network architecture. However, the presence of an enormous number of smart devices in fog networks affects the performance of the network. To harvest the benefits of fog networking necessitates finding optimal cloudlet selection strategies. This article formulates a mixed-integer non-linear programming (MINLP) problem that has the objective of latency minimization. An exhaustive search on our cache-enabled (CE) fog architecture cannot be applied because of the problem’s combinatorial and NP-hard nature. Similarly, the genetic algorithm (GA) cannot be used to find the solution because of the calculation of the number of generations. The increase in the number of IoT and fog nodes increases the solution search space, hence an Outer Approximation Algorithm (OAA) is proposed to arrive at the solution. Low complexity, convergence, and effectiveness of the proposed algorithm ensures the
$\epsilon $
-optimal solution = 10
⁻³
, obtained through standard problem solvers.