Abstract
In the edge computing, service placement refers to the process of installing service platforms, databases, and configuration files corresponding to computing tasks on edge service nodes. In order to meet the latency requirements of new types of applications, service placement in edge computing becomes critical. The service placement strategy must be carried out in accordance with the relevant tasks within the program. However, previous research has paid little attention to related tasks within the application. If the service placement strategy does not consider task relevance, the system will frequently switch services and cause serious system overhead. In this paper, we mainly study the problem of service placement in edge computing. At the same time, we considered the issue of network access point selection during data transmission and the dependencies of task execution. We propose a Dynamic Service Placement List Scheduling (DSPLS) algorithm based on dynamic remaining task service time prediction. We conducted relevant simulation experiments, and our algorithm took the least amount of time to complete the task.
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Acknowledgements
This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grants no.62172142, no. 61602155, and in part by the Scientific and Technological Innovation Team of Colleges and Universities in Henan Province under Grants No. 20IRTSTHN018, and in part by the Key Technologies R & D Program of Henan Province under Grants No. 202102210169 and No. 212102210088, and in part by the Leading Talents of Zhongyuan Science and Technology Innovation under Grants No. 214200510012.
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Xu, J., Zheng, R., Yang, L. et al. Service placement strategy for joint network selection and resource scheduling in edge computing. J Supercomput 78, 14504–14529 (2022). https://doi.org/10.1007/s11227-022-04458-8
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DOI: https://doi.org/10.1007/s11227-022-04458-8