Distributed Redundancy Scheduling for Microservice-based Applications at the Edge
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Multi-access Edge Computing (MEC) is booming as a promising paradigm to push the computation and communication resources from cloud to the network edge to provide services and to perform computations. With container technologies, mobile devices with small memory footprint can run composite microservice-based applications without time-consuming backbone. Service deployment at the edge is of importance to put MEC from theory into practice. However, current state-of-the-art research does not sufficiently take the composite property of services into consideration. Besides, although Kubernetes has certain abilities to heal container failures, high availability cannot be ensured due to heterogeneity and variability of edge sites. To deal with these problems, we propose a distributed redundancy scheduling algorithm, named SAA-RS, for microservice-based applications with sequential combinatorial structure. We formulate a stochastic optimization problem with the uncertainty of microservice request considered, and then decide for each microservice, how it should be scheduled and with how many instances as well as on which edge sites to deploy them. Benchmarks are implemented in two scenarios, where redundancy scheduling is allowed and not, respectively. Numerical results based on a real-world dataset verifies that SAA-RS significantly outperforms four benchmarks by 60.89%, 71.51%, 79.23%, and 84.91%, respectively.
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