Using the Cuckoo Algorithm to Optimizing the Response Time and Energy Consumption Cost of Fog Nodes by Considering Collaboration in the Fog Layer

Task Allocation for Energy Optimization in Fog Computing Networks with Latency Constraints

“…Similarly to [16], delay related to queuing and computing is calculated as an average response time of queuing model (M/M/1 for workload processed in FNs) with a constant value added for transmission delay between FNs. While both works use similar objective functions (weighted sum of energy consumption and delay), [18] includes fairness coefficients that depend on resources available to FNs while [17] does not. The authors conclude that the problem in [17] is convex.…”

“…The authors conclude that the problem in [17] is convex. For [18], they propose a heuristic, population-based algorithm, i.e., cuckoo evolution algorithm. Results of [17] show a clear trade-off between energy consumption and delay in the network.…”

“…Results of [17] show a clear trade-off between energy consumption and delay in the network. The method proposed in [18] decreases both delay and energy consumption compared with a competing algorithm (proposed in [19]), while both works highlight that cooperation between nodes leads to lowered costs.…”

“…Vakilian et al [17], [18] do not consider adjusting CPU frequencies of nodes. Furthermore, offloaded traffic is not divided into a number of requests, packets, or instances in [17], [18].…”

“…Vakilian et al [17], [18] do not consider adjusting CPU frequencies of nodes. Furthermore, offloaded traffic is not divided into a number of requests, packets, or instances in [17], [18]. It is only parameterized with a single number (like in [16]) Hence, [17], [18] differ from our work in aspect (iii)).…”