PDMA: Probabilistic service migration approach for delay‐aware and mobility‐aware mobile edge computing

Mobile edge computing (MEC) pushes computing resources to the edge of the network and distributes them at the edge of the mobile network. Offloading computing tasks to the edge instead of the cloud can reduce computing latency and backhaul load simultaneously. However, new challenges incurred by user mobility and limited coverage of MEC server service arise. Services should be dynamically migrated between multiple MEC servers to maintain service performance due to user movement. Tackling this problem is nontrivial because it is arduous to predict user movement, and service migration will generate service interruptions and redundant network traffic. Service interruption time must be minimized, and redundant network traffic should be reduced to ensure service quality. In this paper, the container live migration technology based on prediction is studied, and an online prediction method based on map data that does not rely on prior knowledge such as user trajectories is proposed to address this challenge in terms of mobility prediction accuracy. A multitier framework and scheduling algorithm are designed to select MEC servers according to moving speeds of users and latency requirements of offloading tasks to reduce redundant network traffic. Based on the map of Beijing, extensive experiments are conducted using simulation platforms and real-world data trace. Experimental results show that our online prediction methods perform better than the common strategy. Our system reduces network traffic by 65% while meeting task delay requirements. Moreover, it can flexibly respond to changes in the user’s moving speed and environment to ensure the stability of offload service.

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Container-Based Fast Service Migration Method for Mobile Edge Computing

Journal of Circuits System and Computers ◽

10.1142/s0218126622501171 ◽

2021 ◽

Author(s):

Xianyu Meng ◽

Wei Lu

Keyword(s):

Dynamic Loading ◽

File System ◽

High Reliability ◽

Rapid Development ◽

Edge Computing ◽

Migration Time ◽

Mobile Edge Computing ◽

Computing Center ◽

Service Migration ◽

Iot Devices

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.

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Dynamic Service Migration and Request Routing for Microservice in Multi-cell Mobile Edge Computing

IEEE Internet of Things Journal ◽

10.1109/jiot.2022.3140183 ◽

2022 ◽

pp. 1-1

Author(s):

Xiangyi Chen ◽

Yuanguo Bi ◽

Xueping Chen ◽

Hai Zhao ◽

Nan Cheng ◽

...

Keyword(s):

Edge Computing ◽

Mobile Edge Computing ◽

Service Migration ◽

Request Routing

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Memetic Algorithm Based on Community Detection for Energy-Efficient Service Migration Optimization in 5G Mobile Edge Computing

10.1109/pimrc50174.2021.9569577 ◽

2021 ◽

Author(s):

Guo Li ◽

Ling Liu ◽

Zhengping Liang ◽

Xiaoliang Ma ◽

Zexuan Zhu

Keyword(s):

Community Detection ◽

Energy Efficient ◽

Memetic Algorithm ◽

Edge Computing ◽

Mobile Edge Computing ◽

Service Migration

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A dynamic service migration strategy based on mobility prediction in edge computing

International Journal of Distributed Sensor Networks ◽

10.1177/1550147721993403 ◽

2021 ◽

Vol 17 (2) ◽

pp. 155014772199340

Author(s):

Lanlan Rui ◽

Shuyun Wang ◽

Zhili Wang ◽

Ao Xiong ◽

Huiyong Liu

Keyword(s):

Optimization Method ◽

Edge Computing ◽

User Mobility ◽

Mobile Edge Computing ◽

Frequent User ◽

Migration Strategy ◽

Service Interruption ◽

Cost Constraints ◽

Initial Location ◽

Service Migration

Mobile edge computing is a new computing paradigm, which pushes cloud computing capabilities away from the centralized cloud to the network edge to satisfy the increasing amounts of low-latency tasks. However, challenges such as service interruption caused by user mobility occur. In order to address this problem, in this article, we first propose a multiple service placement algorithm, which initializes the placement of each service according to the user’s initial location and their service requests. Furthermore, we build a network model and propose a based on Lyapunov optimization method with long-term cost constraints. Considering the importance of user mobility, we use the Kalman filter to correct the user’s location to improve the success rate of communication between the device and the server. Compared with the traditional scheme, extensive simulation results show that the dynamic service migration strategy can effectively improve the service efficiency of mobile edge computing in the user’s mobile scene, reduce the delay of requesting terminal nodes, and reduce the service interruption caused by frequent user movement.

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