Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/16372
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJoseph C.T.
dc.contributor.authorChandrasekaran K.
dc.date.accessioned2021-05-05T10:30:19Z-
dc.date.available2021-05-05T10:30:19Z-
dc.date.issued2020
dc.identifier.citationJournal of Systems Architecture Vol. 111 , , p. -en_US
dc.identifier.urihttps://doi.org/10.1016/j.sysarc.2020.101785
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/16372-
dc.description.abstractThe Information Technology sector has undergone tremendous changes arising due to the emergence and prevalence of Cloud Computing. Microservice Architectures have also been attracting attention from several industries and researchers. Due to the suitability of microservices for the Cloud environments, an increasing number of Cloud applications are now provided as microservices. However, this transition to microservices brings a wide range of infrastructural orchestration challenges. Though several research works have discussed the engineering of microservice-based applications, there is an inevitable need for research on handling the operational phases of the microservice components. Microservice application deployment in containerized datacenters must be optimized to enhance the overall system performance. In this research work, the deployment of microservice application modules on the Cloud infrastructure is first modelled as a Binary Quadratic Programming Problem. In order to reduce the adverse impact of communication latencies on the response time, the interaction pattern between the microservice components is modelled as an undirected doubly weighted complete Interaction Graph. A novel, robust heuristic approach IntMA is also proposed for deploying the microservices in an interaction-aware manner with the aid of the interaction information obtained from the Interaction Graph. The proposed allocation policies are implemented in Kubernetes. The effectiveness of the proposed approach is evaluated on the Google Cloud Platform, using different microservice reference applications. Experimental results indicate that the proposed approach improves the response time and throughput of the microservice-based systems. © 2020 Elsevier B.V.en_US
dc.titleIntMA: Dynamic Interaction-aware resource allocation for containerized microservices in cloud environmentsen_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.