Container-Based Fast Service Migration Method for Mobile Edge Computing

Mobile edge computing (MEC) provides users with low-latency, high-bandwidth, and high-reliability services by migrating the computing power of the cloud computing center to the edge of the network. It is thus being considered an effective solution for the contradiction between the limited computing capabilities of Internet of Things (IoT) devices and the rapid development of delay-sensitive real-time applications. In this study, we propose and design a container union file system based on the differencing hard disk and dynamic loading strategy to address the excessively long migration time caused by the bundling transmission of the file system and container images during container-based service migration. The proposed method involves designing a mechanism based on a remote dynamic loading strategy to avoid the downloading of all container images, thereby reducing the long preparation time before which stateless migration can begin. Furthermore, in view of the excessive latency of the edge service during the stateful migration process, a strategy for avoiding the transmission of the underlying file system and container images is designed to optimize the service interruption time and service quality degradation time. Experiments show that the proposed method and strategy can effectively reduce the migration time of container-based services.

A Dynamic Service Reconfiguration Method for Satellite–Terrestrial Integrated Networks

Satellite–terrestrial integrated networks (STINs) are regarded as a promising solution to meeting the demands of global high-speed seamless network access in the future. Software-defined networking and network function virtualization (SDN/NFV) are two complementary technologies that can be used to ensure that the heterogeneous resources in STINs can be easily managed and deployed. Considering the dual mobility of satellites and ubiquitous users, along with the dynamic requirements of user requests and network resource states, it is challenging to maintain service continuity and high QoE performance in STINs. Thus, we investigate the service migration and reconfiguration scheme, which are of great significance to the guarantee of continuous service provisioning. Specifically, this paper proposes a dynamic service reconfiguration method that can support flexible service configurations on integrated networks, including LEO satellites and ground nodes. We first model the migration cost as an extra delay incurred by service migration and reconfiguration and then formulate the selection processes of the location and migration paths of virtual network functions (VNFs) as an integer linear programming (ILP) optimization problem. Then, we propose a fuzzy logic and quantum genetic algorithm (FQGA) to obtain an approximate optimal solution that can accelerate the solving process efficiently with the benefits of the high-performance computing capacity of QGA. The simulation results validate the effectiveness and improved performance of the scheme proposed in this paper.

Service Migration Algorithm Based On Markov Decision Process With Multiple QoS Attributes

With the rapid development of mobile internet cloud computing, the traditional network structure becomes non-suitable for advanced network traffic requirements. A service migration decision algorithm is proposed in the Software Defined Network(SDN) to satisfy differential Quality of Service(QoS) requirements. We divide services into real-time ones and non-real-time ones due to their different requirements on time delay and transmission rates, and construct the revenue function on two QoS attributes i.e. time delay and available transmission rates. We use the Markov decision process to maximize the overall benefits of users and network system to achieve the best user experience. The simulation results show that our proposed algorithm achieves better performance in terms of overall benefits than the exiting algorithms only considering single service and single QoS attribute.