A Novel Simulated Annealing-based Algorithm for Data Replication Optimization in Mobile Edge Computing

New issues such network congestion, capacity limitation, and excessive latency have arisen due to the everincreasing need for efficiently processing complex data in MEC systems. Improving system performance, lowering latency, or increasing data availability are all possible outcomes of data replication, which entails making several copies of data at the edge nodes. Data replication and placement in MEC systems is hardly a walk in the park, either, since mobile networks are always evolving. An article introducing a heuristic Data Replication Algorithm (SA-DRA) based on Simulated Annealing that is particular to MEC is presented now. Therefore, SA-DRA’s goal is to delay replication until it returns maximum benefit while simultaneously eliminating the use of available network resources. Multiple elements or measurements may be used for this purpose, such as user mobility, network design, and workload kinds. A new solution is first generated using a basic formula, and then a cost function depending on the network status in real mode is used. Sequential operation of surrounding states exploration in a cycle improves the position even farther than the initial result. To find out how much more efficient SA-DRA is at tackling latency and load balancing between edge nodes, we compared the simulated results to those of using heuristics and greed.