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The number of smartphone users and mobile devices has increased significantly. The Mobile Cloud Applications based on cloud computing have also been increased. The mobile apps can be used in Augmented Reality, E-Transportation, 2D/3-D Games, E-Healthcare, and Education. The modern cloud-based frameworks provide such services on Virtual Machines. The existing frameworks worked well, but these suffered the problems such as overhead, resource utilization, lengthy boot-time, and cost of running Mobile Applications. This study addresses these problems by proposing a Dynamic Decision-Based Task Scheduling Technique for Microservice-based Mobile Cloud Computing Applications (MSCMCC). The MSCMCC runs delay-sensitive applications and mobility with less cost than existing approaches. The study focused on Task Scheduling problems on heterogeneous Mobile Cloud servers. We further propose Task Scheduling and Microservices based Computational Offloading (TSMCO) framework to solve the Task Scheduling in steps, such as Resource Matching, Task Sequencing, and Task Scheduling. Furthermore, the experimental results elaborate that the proposed MSCMCC and TSMCO enhance the Mobile Server Utilization. The proposed system effectively minimizes the cost of healthcare applications by 25&#x0025;, augmented reality by 23&#x0025;, E-Transport tasks by 21&#x0025;, and 3-D games tasks by 19&#x0025;, the average boot-time of microservices applications by 17&#x0025;, resource utilization by 36&#x0025;, and tasks arrival time by 16&#x0025;.

A Cost and Energy Efficient Task Scheduling Technique to Offload Microservices Based Applications in Mobile Cloud Computing