A Fuzzy-Based Mobile Edge Architecture for Latency-Sensitive and Heavy-Task Applications

Appropriate task offloading management strategy is a challenging problem for high delay-sensitive and heavy-task applications. This paper proposes fuzzy-based mobile edge manager with partitioning, which can handle the multi-criteria decision-making process by considering multiple parameters in MEC network framework make appropriate decisions incoming tasks of IoT Considering that devices are becoming more powerful, this also takes WLAN delay computing power into account, forming three-level fuzzy logic system. In addition, since many Internet Things applications composed several independent modules, sets two optimal partitioning ratios, have symmetry, so each module be independently executed layer network. results will return to after execution, as minimize service time improve QoS. Finally, indexes such failure rate simulated, show proposed scheme has better performance compared other four comparison schemes, especially high-latency sensitivity