Data Transmission Optimization And Intelligent Offloading Strategy In Cloud Computing

Smart phones and the development of various mobile devices bring a lot of convenience, however, at the same time, we also criticized in some of the problems of mobile devices, such as storage capacity, limited battery life. Mobile users’ experience is pressing for a new round of innovation. Cloud computing can improve the mobile computing power as well as reduce the energy consumption of mobile terminals. However, in fact, the data in the process of offloading to the cloud, also need to consume the transmission power of the mobile terminal, and in some cases, the transmission power even greater than local computing power consumption. Most people only see the development of wireless network technology to bring convenience, but without being aware of the information technology to the environment pollution and destruction, the mobile terminal equipment, and other information technology infrastructure consumes a lot of power, a heavy burden to the grid, which also contributed to the greenhouse gas emissions.In order to reduce the energy consumption of mobile terminals, make cloud computing more energy saving, this paper mainly studied the following contents:(1) Studying the wireless transmission network, in which the energy efficiency and spectrum efficiency represent the optimization problem. Traditional wireless network optimization problem is a single optimal, energy efficiency or spectrum efficiency, which will result the low resource efficiency. In order to make the network get a better utilization of the resource, this paper studies the unified spectrum efficiency and energy efficiency problem This paper proposes a new joint efficiency and spectrum efficiency of network performance metrics- resource efficiency. Based on the research of the nature of the resource efficiency, this paper gives two kinds of optimal resource efficiency of network resources allocation policy. By simulation comparing, the joint optimization strategy is feasible.(2) Studying the problem of data transfer and offloading in cloud computing. Cloud computing can assist mobile users computing tasks, reducing the burden of the mobile terminals, however, as the data offloading to the cloud will consume resource of the mobile terminal, when the transmission power is greater than the local computing power consumption, cloud computing will lose its ability to reduce the power consumption of mobile terminal, and even intensified the energy consumption on mobile. In this paper, we applied the joint optimization of resource allocation in wireless transmission strategy to cloud computing data transmission, reducing the power consumption of data transmission. And combing with cloud computing power consumption model, this paper put forward a uninstall the optimization problem of data in cloud computing, move to save the energy consumption for the purpose of the system according to the practical calculation of choice under the condition of the local task execution or the clouds, raise the scientific nature of the cloud computing and energy saving. The simulation results confirmed the necessity and feasibility of data offloading strategy.