A Survey of Computation Offloading for Mobile Systems using WSM method

The introduction delves, such as limited battery life, memory, which hinder their ability to handle complex computations efficiently. To address these challenges, computation offloading emerges as a promising technique that involves transferring computation tasks from mobile devices to more powerful remote resources, such as cloud servers or edge nodes. By offloading tasks, mobile devices can conserve energy, improve performance, and extend their capabilities. the concept of computation offloading is not entirely new, but recent advancements in mobile communication technologies and cloud computing have revitalized research interest in this area. Overall, the introduction sets the stage for the survey by emphasizing the importance of computation offloading in the mobile systems domain, and it outlines the scope and objectives of the study in providing a comprehensive overview of this critical research area. Computation offloading can lead to improved user experiences by reducing latency, enhancing responsiveness, and enabling seamless execution of resource-intensive applications on mobile devices. Mobile devices often have limited processing power and battery life. Research in computation offloading can provide strategies to alleviate these constraints by offloading tasks to more powerful servers or cloud resources. the research significance lies in its potential to shape the future of mobile computing by optimizing performance, energy efficiency, and user experiences while addressing the challenges of resource constraints and dynamic network conditions. In the weighted amount approach, each of our goals by the weight provided by the user multiply our goals the package is the only goal we measure. This time very widely used one of the approaches. Weighted amount approaches mind that comes to mind when done the question is, for every goal what weights should be assigned doing the same. Multi-departural optimization in trouble, we have many objectives there are functions; they are we we want to increase or reduce. Many obstacles to our problem there are, they are our potential to complement any solutions should. These issues global parato package we are trying to find out. Global parato-approved package, often pareto-flexible referred to as package, points that do not have other points package, then these points and yet our potential best in the region. Alternative parameters taken as Video, Gaming, VolP, Data. Evaluation parameters taken as 2016, 2017, 2018, 2019, 2020. From the result it is seen that 2020 is got the first rank where as is the 2018 having the lowest rank. The first ranking 2020 is obtained with the lowest quality of compensation