Sustainable task scheduling strategy in cloudlets

Cloudlet is an important part of providing cloud services in Mobile Edge Computing (MEC) with sustainability. As the number of mobile users grows rapidly in the current era, the load in the cloudlet becomes very high. The cloudlet is considered in the middle layer for providing cloud services with low latency and energy efficiency. Hence the task allocation and scheduling inside of the cloudlet is a challenging job. In the recent past, many research works conducted without considering real-time network parameters. In this work, a heuristic load balancing strategy is designed and analyzed to minimize the task completion time and makespan, which enhances the efficiency of cloud services. The proposed method is considered a dynamic task allocation strategy to the cloudlet concerning network bandwidth, network delay, energy efficiency, and this approach is compared with the queue-based task allocation strategy. The experiment is conducted to compare the proposed method with the recently developed standard algorithms over the synthetic dataset. Experimental results of the proposed work show a significant improvement in task scheduling in terms of energy and execution cost, as well as time, compared to the existing methods. The proposed method outperforms the standard algorithm in most of the observed cases with sustainability.

Automated summary

Cloudlet plays an essential role in providing cloud services in Mobile Edge Computing (MEC) with sustainability, aiming at low latency and energy efficiency. A heuristic load balancing strategy is designed to minimize task completion time and makespan, enhancing cloud service efficiency. Experimental results demonstrate significant improvement in energy and execution cost, as well as time, compared to existing methods, with the proposed method outperforming standard algorithms in most observed cases.