International Journal of Communication Systems, Год журнала: 2024, Номер unknown
Опубликована: Ноя. 18, 2024
ABSTRACT The wireless intelligent computing paradigm has significantly provided services to various sectors in today's technology‐driven landscape. Despite its popularity, faces challenges addressing time‐sensitive tasks due the physical distance between servers from users. Edge been introduced for internet of things (IoT) as an effective complement enhance capacity handling latency‐critical tasks. However, limited resources IoT and edge nodes can lead suboptimal task management. In response these challenges, we propose a lightweight approach that leverages hybrid technique combining whale optimization algorithm (WOA) with adaptive inertia weight genetic component. This method aims efficiency offloading cloud‐edge environment. Experimental results demonstrate proposed strategy not only addresses limitations traditional methods but also achieves significant improvements, 34% increase makespan minimization, 11% reduction rejection ratio, 17% decrease execution cost, 15% improvement energy utilization compared WOAs. simulation highlight effectiveness enhancing quality service (QoS) metrics latency‐sensitive applications.
Язык: Английский