14,905 research outputs found
Transparent Orchestration of Task-based Parallel Applications in Containers Platforms
This paper presents a framework to easily build and execute parallel applications in container-based distributed computing platforms in a user-transparent way. The proposed framework is a combination of the COMP Superscalar (COMPSs) programming model and runtime, which provides a straightforward way to develop task-based parallel applications from sequential codes, and containers management platforms that ease the deployment of applications in computing environments (as Docker, Mesos or Singularity). This framework provides scientists and developers with an easy way to implement parallel distributed applications and deploy them in a one-click fashion. We have built a prototype which integrates COMPSs with different containers engines in different scenarios: i) a Docker cluster, ii) a Mesos cluster, and iii) Singularity in an HPC cluster. We have evaluated the overhead in the building phase, deployment and execution of two benchmark applications compared to a Cloud testbed based on KVM and OpenStack and to the usage of bare metal nodes. We have observed an important gain in comparison to cloud environments during the building and deployment phases. This enables better adaptation of resources with respect to the computational load. In contrast, we detected an extra overhead during the execution, which is mainly due to the multi-host Docker networking.This work is partly supported by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316 project, by the Generalitat de Catalunya under contracts 2014-SGR-1051 and 2014-SGR-1272, and by the European Union through the Horizon 2020 research and innovation program under grant 690116 (EUBra-BIGSEA Project). Results presented in this paper were obtained using the Chameleon testbed supported by the National Science Foundation.Peer ReviewedPostprint (author's final draft
Real-Time Containers: A Survey
Container-based virtualization has gained a significant importance in a deployment of software applications in cloud-based environments. The technology fully relies on operating system features and does not require a virtualization layer (hypervisor) that introduces a performance degradation. Container-based virtualization allows to co-locate multiple isolated containers on a single computation node as well as to decompose an application into multiple containers distributed among several hosts (e.g., in fog computing layer). Such a technology seems very promising in other domains as well, e.g., in industrial automation, automotive, and aviation industry where mixed criticality containerized applications from various vendors can be co-located on shared resources.
However, such industrial domains often require real-time behavior (i.e, a capability to meet predefined deadlines). These capabilities are not fully supported by the container-based virtualization yet. In this work, we provide a systematic literature survey study that summarizes the effort of the research community on bringing real-time properties in container-based virtualization. We categorize existing work into main research areas and identify possible immature points of the technology
Server Structure Proposal and Automatic Verification Technology on IaaS Cloud of Plural Type Servers
In this paper, we propose a server structure proposal and automatic
performance verification technology which proposes and verifies an appropriate
server structure on Infrastructure as a Service (IaaS) cloud with baremetal
servers, container based virtual servers and virtual machines. Recently, cloud
services have been progressed and providers provide not only virtual machines
but also baremetal servers and container based virtual servers. However, users
need to design an appropriate server structure for their requirements based on
3 types quantitative performances and users need much technical knowledge to
optimize their system performances. Therefore, we study a technology which
satisfies users' performance requirements on these 3 types IaaS cloud. Firstly,
we measure performances of a baremetal server, Docker containers, KVM (Kernel
based Virtual Machine) virtual machines on OpenStack with virtual server number
changing. Secondly, we propose a server structure proposal technology based on
the measured quantitative data. A server structure proposal technology receives
an abstract template of OpenStack Heat and function/performance requirements
and then creates a concrete template with server specification information.
Thirdly, we propose an automatic performance verification technology which
executes necessary performance tests automatically on provisioned user
environments according to the template.Comment: Evaluations of server structure proposal were insufficient in section
Evaluation of e-learning web sites using fuzzy axiomatic design based approach
High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered
On the Use of Kernel Bypass Mechanisms for High-Performance Inter-container Communications
In this paper, we perform a comparison among a number of different virtual bridging and switching technologies, each widely available and commonly used on Linux, to provide network connectivity to co-located LXC containers for high-performance application scenarios
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