A placement architecture for a container as a service (CaaS) in a cloud environment

Mohamed K Hussein,Mohamed H Mousa,Mohamed A Alqarni

doi:10.1186/s13677-019-0131-1

Mohamed K Hussein, Mohamed H Mousa + Show 1 more

Open Access

https://doi.org/10.1186/s13677-019-0131-1

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Abstract

Unlike a traditional virtual machine (VM), a container is an emerging lightweight virtualization technology that operates at the operating system level to encapsulate a task and its library dependencies for execution. The Container as a Service (CaaS) strategy is gaining in popularity and is likely to become a prominent type of cloud service model. Placing container instances on virtual machine instances is a classical scheduling problem. Previous research has focused separately on either virtual machine placement on physical machines (PMs) or container, or only tasks without containerization, placement on virtual machines. However, this approach leads to underutilized or overutilized PMs as well as underutilized or overutilized VMs. Thus, there is a growing research interest in developing a container placement algorithm that considers the utilization of both instantiated VMs and used PMs simultaneously.The goal of this study is to improve resource utilization, in terms of number of CPU cores and memory size for both VMs and PMs, and to minimize the number of instantiated VMs and active PMs in a cloud environment. The proposed placement architecture employs scheduling heuristics, namely, Best Fit (BF) and Max Fit (MF), based on a fitness function that simultaneously evaluates the remaining resource waste of both PMs and VMs. In addition, another meta-heuristic placement algorithm is proposed that uses Ant Colony Optimization based on Best Fit (ACO-BF) with the proposed fitness function. Experimental results show that the proposed ACO-BF placement algorithm outperforms the BF and MF heuristics and maintains significant improvement of the resource utilization of both VMs and PMs.

Highlights

Cloud computing is the on-demand delivery of computing applications, storage and infrastructure as services provided to customers over the Internet
Cloud services are typically provided in three different service models: (1) Infrastructure as a Service (IaaS), which is a computing infrastructure in which storage and computing hardware are provided through API and web portals; (2) Platform as a Service (PaaS), which is a platform for application development provided as services, such as scripting environments and database services
Two scheduling algorithms, including the heuristic Max Fit and Best Fit algorithm as well as the meta-heuristic Ant Colony Optimization (ACO), are tested using a fitness function that analyzes the percentage of remaining resources that are wasted in the physical machines (PMs) and Virtual machines (VMs)

Summary

Introduction

Cloud computing is the on-demand delivery of computing applications, storage and infrastructure as services provided to customers over the Internet. Virtual machine (VM) technology is the leading execution environment used in cloud computing. A virtual machine is an emulation of physical hardware resources that runs an independent operating system on top of a VMM, called a hypervisor. Docker Containerization is considered lightweight for two main reasons: (1) it significantly decreases container startup times because the containers do not require launching a VM or an operating system, and (2) communications are performed through system calls using the shared operating system kernel—unlike the heavyweight communication performed by a virtual machine hypervisor

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