TY  - JOUR
PB  - Springer Science and Business Media Deutschland GmbH
SN  - 18761100
EP  - 706
AV  - none
TI  - Towards Early Distribution of Container-Based Microservices in Cloud Computing Environment
SP  - 699
N1  - cited By 0; Conference of 1st International Conference on Artificial Intelligence for Smart Community, AISC 2020 ; Conference Date: 17 December 2020 Through 18 December 2020; Conference Code:286319
Y1  - 2022///
VL  - 758
JF  - Lecture Notes in Electrical Engineering
A1  - Saboor, A.
A1  - Mahmood, A.K.
A1  - Hassan, M.F.
A1  - Shah, S.N.M.
A1  - Siddiqui, M.A.
A1  - Magsi, S.A.
A1  - Junaid, M.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142723199&doi=10.1007%2f978-981-16-2183-3_67&partnerID=40&md5=e082ea915d4d1e7812f4a83ed052509e
ID  - scholars17390
KW  - Cloud applications; Cloud computing environments; Cloud/edge computing; Datacenter; Design Patterns; Edge computing; Microservice; Network communications; Optimisations; Random distribution
KW  -  Containers
N2  - Microservices gained the popularity for use in scalable cloud application. The application based on microservices uses intensive network communication to call other microservices or to pass on the messages to hundreds of microservices running inside the cloud/edge nodes. This study addressed the early distribution of container-based microservices and proposed two distribution strategies named as Random Distribution and Design Pattern Distribution. In random distribution approach the microservices are assigned arbitrarily to the available data centers. While in design pattern distribution the microservices are grouped together on the basis of behavioral design patterns which identifies common communication patterns among objects. The proposed solution was tested using custom built simulation environment and the results showed that the early distribution of microservices according to the design pattern of the application resulted in significant reduction of network calls to the microservices hosted at other network nodes or data centers. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ER  -