The use of containers in cloud architectures has become widespread, owing to advantages such as limited overheads, easier and faster deployment, and higher portability. Moreover, they present a suitable architectural solution for the deployment of applications created using a microservice development pattern. But the remain open issue is that ----- container resource allocation influences system performance and resource consumption, and so it is a key factor for cloud providers. In this paper, they propose a genetic algorithm approach, using the Non-dominated Sorting Genetic Algorithm 2
Cloud computing and virtualization technologies play important roles in modern service-oriented computing paradigm. More conventional services are being migrated to virtualized computing environments to achieve flexible deployment and high availability.
There are many computer controlled applications where delays in critical processing can have undesirable, or even disastrous consequences. A real-time system is one whose correctness depends on timing as well as functionality.
Computer Scientists have known about these types of queries for a long time, but not much attention was paid to the impact of these queries until the Internet exploded and Big Data reared its ugly head.
This paper presents a study of ACO to implement a new scheduler for docker. The main contribution of this paper is an ACO-based algorithm, which distributes application containers over Docker hosts. It is to balancing the resource and finally leads to the better performance of applications.