Research On Energy Saving Strategy Of Mobile Devices Based On Cloud Environment

In today,with the rapid popularization of smart phones and the extensive development of application software,mobile phones have become an indispensable part of life.But in the process of using,people find that the problem of mobile energy consumption is more and more serious,and the lag of hardware performance improvement further restricts its development.Therefore,the current system often from the perspective of software,using mobile cloud computing to solve the problem of lack of mobile energy.Specifically,the mobile end transfers some tasks to the cloud or edge nodes through the system task scheduling,and returns the calculation results to reduce the local energy consumption of the mobile end.However,it should be noted that such migration calculation will generate additional time consumption.Therefore,how to reasonably carry out application migration to ensure the quality of service of users and reduce the energy consumption of mobile devices is an urgent problem for mobile cloud computing.In this regard,this thesis puts forward two solutions:Firstly,we propose a based cloud of computing migration system.In the mobile cloud computing environment,the system has multiple access nodes with different computing capabilities,and the energy consumption of these nodes is different due to the quality of service.In the background of this thesis,the system can selectively use local,multiple different computing points and cloud to process tasks.Therefore,the new system proposed in this thesis can find a most suitable solution for user among multiple tasks and multiple computing points.In order to speed up the search of the final optimal solution,this thesis also uses an improved genetic algorithm,its specific advantage is that it can be more suitable for the target value search in the migration algorithm,accelerate convergence and improve accuracy.The simulation results show that the strategy in this thesis can complete the scheduled tasks well and reduce the energy consumption and time index in the whole process.Secondly,we propose a multi-user migration algorithm.In the real environment,in order to reduce the cost and facilitate the management,cloud service providers usually schedule multiple users to use cloud resources together.In such a scenario,new challenges are put forward to the original system.To begin with,based on the protocol between cloud provider and user,this thesis groups multi-user,and the service levels of different groups are different.Then through the dynamic cloud resource division strategy,on the one hand,improve the priority of advanced user groups,enhance the enthusiasm of users to pay for additional services.On the other hand,it also guarantees the basic needs of ordinary user groups.Experiments show that the strategy can meet the requirements of different user groups.