SRAF: A Service-Aware Resource Allocation Framework for VM Management in Mobile Data Networks

Abstract

Service latency and resource utilization are the key factors which limit the development of mobile data networks. To this end, we present a service-aware resource allocation framework, called SRAF, to allocate the basic resources by managing virtual machine (VM). In SRAF, we design two new methods for better virtual machine (VM) management. Firstly, we propose the self-learning classification algorithm (SCA) which executes the service request classification. Then, we use the classification results to schedule different types of VMs. Secondly, we design a sharing mode to jointly execute service requests, which can share the CPU and bandwidth simultaneously. In order to enhance the utilization of resources with the sharing mode, we also design two scaling algorithms, i.e., the horizontal scaling and the vertical scaling, which execute the operation of resource-level scaling and VM-level scaling, respectively. Furthermore, to enhance the stability of SRAF and avoid the frequent operation of scaling, we introduce a Markov decision process (MDP) to control VM migration. The experimental results reveal that SRAF greatly reduces service latency and enhances resource utilization. In addition, SRAF also has a good performance on stability and robustness for different situations of congestion.

Research on the Innovation of Science and Technology Management Data Service Mode under Artificial Intelligence Technology

“…Most of the data service platforms only provide simple data-sharing functions, and only a very small number of them are involved in the preliminary interpretation of the data and analysis services; these traditional and the most basic data services can not better serve scientific and technological decision-making. In addition, the main body of science and technology innovation needs, now is the era of a knowledge economy, science and technology innovation activities are increasingly prosperous, government departments, science and technology innovation main body of science and technology management work more and more goals and needs, science and technology management data needs are no longer limited to access to basic data [4][5]. The personalized and intelligent needs of science and technology users continue to emerge, and the existing passive data services are far from being able to meet the needs of the main body of science and technology innovation.…”