Research On Resource Management Technology For Mobile Cloud

Mobile cloud computing combines cloud computing with mobile Internet technology to achieve complementary advantages,bringing more convenient cloud services to mobile users.Mobile users can migrate data computing and storage to the cloud to improve their mobile terminal processing capacity,small storage space and short power life.Question.However,due to the characteristics of mobile users such as distribution and mobility,service applications and exits are often uncertain and users require higher quality of service,resulting in frequent and random resource scheduling,which brings new challenges to the resource management of mobile cloud computing center.How to manage the resources of mobile cloud computing data center dynamically and rationally and maximize the utility of the data center while ensuring the quality of service is also one of the key issues in the field of mobile cloud computing.The major innovations in this analysis are the features of mobile cloud computing data centers resource allocation,and systematically and closely studies the resource scheduling,load forecasting and fault tolerance mechanisms of mobile cloud computing.:(1)To solve the high energy consumption problem of mobile cloud data centers,a resource model and a dynamic energy consumption model of mobile cloud data centers are established.Based on this model,a four-dimensional virtual resource scheduling algorithm(FVRSA)for Mobile cloud computing is proposed.The resource allocation process is divided into three phases: initial resource allocation,dynamic resource scheduling,and global resource optimization.We also design three optimization algorithms aiming to minimize the energy consumption in the three phases.Model and algorithms by conducting simulation experiments.Experimental results show that compared with similar algorithms,this algorithm can effectively reduce the energy consumption of cloud data center,and can meet the service level protocol SLA to the maximum extent.(2)To reduce the energy consumption of mobile cloud data centers while improving the effectiveness of data centers,a virtual machine scheduling model VMSA-EU was established based on multi-objective optimization technology.Aiming to minimize the energy consumption and maximize utility of data The experimental results show that the proposed algorithms have better performances in both scheduling time and the NSGAII-based virtual machine scheduling algorithm was proposed to solve the model.The effectiveness of the model and algorithms are verified by simulation experiments comparing with similar algorithms.Scheduling results.(3)To solve the host load forecasting problem in mobile cloud computing,the wavelet support vector regression model is introduced to establish a hybrid wavelet support vector regression host load forecasting algorithm.By studying the load data of the mobile cloud computing data center hosts,The simulation of the prediction of load data based on the wavelet support vector regression model.By solving the model parameters using the firefly swarm optimization algorithm,the prediction accuracy of the model is increased.In the simulation experiments,the proposed algorithm is compared with similar prediction algorithms.The Experimental results show that the proposed prediction algorithm is better than the similar prediction algorithms in prediction accuracy.(4)To improve the usability of mobile cloud data centers,we improved the ARMA model.A double-layer heartbeat detection model and double-layer heartbeat detection algorithm(DLHB)for mobile cloud computing are proposed.The algorithm is composed of ARIMA-Based on inter-domain heartbeat prediction algorithm and the intra-domain heartbeat detection algorithm.Experimental results show that the proposed DLHB algorithm can detect multiple node failures at the same time within a shorter detection time.(5)Aiming at the application requirement of warship field,this paper designs the overall architecture,logical architecture and overall flow of mobile private cloud resource management platform for warship formation based on relevant theories,and preliminarily constructs the warship mobile cloud resource management platform.The proposed model and algorithms are implemented and tested.The functions and performance of the platform are also Tested and analyzed.