scholarly journals The Effect of the Resource Consumption Characteristics of Cloud Applications on the Efficiency of Low-Metric Auto Scaling Solutions

2018 ◽  
Vol 8 (1/2/3/4/5) ◽  
pp. 01-09
Author(s):  
Ha Van Cu ◽  
Nguyen Hong Son
Keyword(s):  
Resource Consumption ◽  
Auto Scaling ◽  
Cloud Applications

On minimizing the resource consumption of cloud applications using process migrations

2013 ◽  
Vol 73 (12) ◽  
pp. 1690-1704 ◽  
Author(s):  
Nikos Tziritas ◽  
Samee Ullah Khan ◽  
Cheng-Zhong Xu ◽  
Thanasis Loukopoulos ◽  
Spyros Lalis
Keyword(s):  
Resource Consumption ◽  
Cloud Applications

scholarly journals TOSCA-Based and Federation-Aware Cloud Orchestration for Kubernetes Container Platform

2019 ◽  
Vol 9 (1) ◽  
pp. 191 ◽  
Author(s):  
Dongmin Kim ◽  
Hanif Muhammad ◽  
Eunsam Kim ◽  
Sumi Helal ◽  
Choonhwa Lee
Keyword(s):  
Service Providers ◽  
Research Work ◽  
Cloud Service ◽  
Daunting Task ◽  
Cloud Service Providers ◽  
Service Areas ◽  
Sample Application ◽  
Container Orchestration ◽  
Auto Scaling ◽  
Cloud Applications

Kubernetes, a container orchestration tool for automatically installing and managing Docker containers, has recently begun to support a federation function of multiple Docker container clusters. This technology, called Kubernetes Federation, allows developers to increase the responsiveness and reliability of their applications by distributing and federating container clusters to multiple service areas of cloud service providers. However, it is still a daunting task to manually manage federated container clusters across all the service areas or to maintain the entire topology of cloud applications at a glance. This research work proposes a method to automatically form and monitor Kubernetes Federation, given application topology descriptions in TOSCA (Topology and Orchestration Specification for Cloud Applications), by extending the orchestration tool that automatizes the modeling and instantiation of cloud applications. It also demonstrates the successful federation of the clusters according to the TOSCA specifications and verifies the auto-scaling capability of the configured system through a scenario in which the servers of a sample application are deployed and federated.

scholarly journals IAAS Reactive Auto Scaling Performance Challenges

2019 ◽  
Vol 8 (10) ◽  
pp. 538-541
Keyword(s):  
Quality Of Service ◽  
Virtual Machines ◽  
Performance Estimation ◽  
After Effects ◽  
Cloud Application ◽  
Performance Challenges ◽  
Auto Scaling ◽  
Cloud Applications

The principle highlight of a cloud application is its versatility. Significant IaaS cloud administrations suppliers (CSP) utilize auto scaling on the dimension of virtual machines (VM). Other virtualization arrangements (for example compartments, units) can likewise scale. An application scales in light of progress in watched measurements, for example in CPU use. Every so often, cloud applications display the powerlessness to meet the Quality of Service (QoS) necessities during the scaling brought about by the reactivity of auto scaling arrangements. This paper gives the after effects of the auto scaling execution assessment for two-layered virtualization (VMs and units) directed in the open billows of AWS, Microsoft and Google utilizing the methodology and the Auto scaling Performance Estimation Tool created by the creators

The Impact of Anchoring and Warnings on Resource Consumption

2007 ◽  
Author(s):  
Heather Barnes Truelove ◽  
Jeff Joireman ◽  
Donelle C. Posey ◽  
Adrian Spencer ◽  
Nicole Hoffer
Keyword(s):  
Resource Consumption ◽  
The Impact

Hybrid Auto-Scaling Mechanism for Dynamic Load Change

2017 ◽  
Vol 137 (3) ◽  
pp. 521-531
Author(s):  
Yoko Hirashima ◽  
Kenta Yamasaki ◽  
Tomohiro Morimura ◽  
Norihisa Komoda
Keyword(s):  
Dynamic Load ◽  
Load Change ◽  
Auto Scaling
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