Gated Recurrent Unit with Adaptive Golden Jackle Optimization based Efficient Resource Scheduling in Mobile Cloud Computing

Mobile Cloud Computing (MCC) has become the developing technology, where the mobile computing is combined with Cloud Computing (CC) to progress the mobile data. Though the benefits of MCC, but it faces some challenges such as energy consumption, makespan, resource utilization and so on. In this research, Gated Recurrent Unit with Adaptive Golden Jackle Optimization (GRU-AGJO) algorithm is proposed for the energy efficient resource scheduling in MCC. The proposed GRU-AGJO approach efficiently addresses the problem energy consumption, makespan, and resource utilization. The experimental results shows that the proposed GRU-AGJO attains better results and it is estimated by various assessment metrices like makespan, Resource Utilization (RU), Response Time (RT) and Energy Consumption (EC) with the number of tasks of 50 and 100 respectively. The proposed GRU-AGJO approach achieved the minimum makepsan of 29s and 50s in the number of tasks of 50 and 100 when compared to the previous studies like Spider Monkey Optimization (SMO) and Whale Optimization Algorithm (WOA).