Reducing the network overhead of user mobility-induced virtual machine migration in mobile edge computing

2018 ◽  
Vol 49 (4) ◽  
pp. 673-693 ◽  
Author(s):  
Fei Zhang ◽  
Guangming Liu ◽  
Bo Zhao ◽  
Xiaoming Fu ◽  
Ramin Yahyapour
Keyword(s):  
Virtual Machine ◽  
Edge Computing ◽  
User Mobility ◽  
Mobile Edge Computing ◽  
Virtual Machine Migration ◽  
Network Overhead

scholarly journals Virtual Machine Migration Strategy Based on Multi-Agent Deep Reinforcement Learning

2021 ◽  
Vol 11 (17) ◽  
pp. 7993
Author(s):  
Yu Dai ◽  
Qiuhong Zhang ◽  
Lei Yang
Keyword(s):  
Reinforcement Learning ◽  
Virtual Machine ◽  
Control Method ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Centralized Control ◽  
Virtual Machine Migration ◽  
Migration Strategy ◽  
Computing Power ◽  
Multi Agent

Mobile edge computing is a new computing model, which pushes cloud computing power from centralized cloud to network edge. However, with the sinking of computing power, user mobility brings new challenges: since it is usually unstable, services should be dynamically migrated between multiple edge servers to maintain service performance, that is, user-perceived latency. Considering that Mobile Edge Computing is a highly distributed computing environment and it is difficult to synchronize information between servers, in order to ensure the real-time performance of the migration strategy, a virtual machine migration strategy based on Multi-Agent Deep Reinforcement Learning is proposed in this paper. The method of centralized training and distributed execution is adopted, that is, the transfer action is guided by the global information during training, and only the local observation information is needed to obtain the transfer action. Compared with the centralized control method, the proposed method alleviates communication bottleneck. Compared with other distributed control methods, this method only needs local information, does not need communication between servers, and speeds up the perception of the current environment. Migration strategies can be generated faster. Simulation results show that the proposed strategy is better than the contrast strategy in terms of convergence and energy consumption.

scholarly journals A Virtual Machine Migration Strategy Based on the Relevance of Services against Side-Channel Attacks

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Ji-Ming Chen ◽  
Shi Chen ◽  
Xiang Wang ◽  
Lin Lin ◽  
Li Wang
Keyword(s):  
Internet Of Things ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Edge Computing ◽  
Security And Privacy ◽  
Side Channel ◽  
Virtual Machine Migration ◽  
Side Channel Attacks ◽  
Migration Strategy ◽  
Vm Migration

With the rapid development of Internet of Things technology, a large amount of user information needs to be uploaded to the cloud server for computing and storage. Side-channel attacks steal the private information of other virtual machines by coresident virtual machines to bring huge security threats to edge computing. Virtual machine migration technology is currently the main way to defend against side-channel attacks. VM migration can effectively prevent attackers from realizing coresident virtual machines, thereby ensuring data security and privacy protection of edge computing based on the Internet of Things. This paper considers the relevance between application services and proposes a VM migration strategy based on service correlation. This strategy defines service relevance factors to quantify the degree of service relevance, build VM migration groups through service relevance factors, and effectively reduce communication overhead between servers during migration, design and implement the VM memory migration based on the post-copy method, effectively reduce the occurrence of page fault interruption, and improve the efficiency of VM migration.

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

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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