Microservice based architecture for the genetic algorithm
Date Issued
2018
Author(s)
Stevanoska, Evgenija
Spirovski, Kristijan
Petkovski, Goran
Abstract
Microservice architecture is becoming more popular
and more frequently used, mainly because of its numerous advantages over monolith approach. Namely, the developed systems
nowadays need more agile distribution of the processing power,
and due to their size, a way to deploy, maintain and test individual
components separately. Each algorithm/software composed of
individual and independently executable parts that do not share
many parameters are good candidates for a solution based on
a microservice architecture. This paper presents a microservice
approach when building an architecture for the genetic algorithm.
We identified eight independent parts of the genetic algorithm,
and each one is represented as a microservice. This design leads
to a solution that has low coupling and high cohesion. The advantages of this approach include distributing the computations on
more physical locations, and furthermore, scaling only the parts
of the system which require more performance (which means
need large processing power or are frequently executed).
and more frequently used, mainly because of its numerous advantages over monolith approach. Namely, the developed systems
nowadays need more agile distribution of the processing power,
and due to their size, a way to deploy, maintain and test individual
components separately. Each algorithm/software composed of
individual and independently executable parts that do not share
many parameters are good candidates for a solution based on
a microservice architecture. This paper presents a microservice
approach when building an architecture for the genetic algorithm.
We identified eight independent parts of the genetic algorithm,
and each one is represented as a microservice. This design leads
to a solution that has low coupling and high cohesion. The advantages of this approach include distributing the computations on
more physical locations, and furthermore, scaling only the parts
of the system which require more performance (which means
need large processing power or are frequently executed).
Subjects
File(s)![Thumbnail Image]()
Loading...
Name
CIIT2018.pdf
Size
708.71 KB
Format
Adobe PDF
Checksum
(MD5):612fd5a4527260efda1a3ff28997b260