Open AccessImplementing a Software Load Balancer with a Genetic Algorithm
Author(s) -
Curcă Alexandru
Publication year - 2020
Publication title -
scientific bulletin
Language(s) - English
Resource type - Journals
eISSN - 2392-8956
pISSN - 1454-864X
DOI - 10.21279/1454-864x-20-i2-024
Subject(s) - scalability , computer science , forwarding plane , python (programming language) , software defined networking , virtualization , distributed computing , network topology , software , load balancing (electrical power) , network virtualization , openflow , network functions virtualization , operating system , computer network , cloud computing , geometry , mathematics , network packet , grid
In the context of network evolution, concepts like Software Defined Networking (SDN) and Network Functions Virtualisation (NFV) appeared on the market. Network virtualization permits the implementation of routers, switches and load balancers in software and separation of control plane and data plane brings easier configuration, implementation and scalability. The monolithic design of traditional network devices can be changed by implementing new algorithms which will improve the overall system performance. An example is our Software Load Balancer with a Genetic Algorithm. The code written in Python is functional through the POX Controller and the advantages of evolutionary algorithms make this implementation an innovative solution for dynamically modified topologies.