scholarly journals Correction to: Severity: a QoS-aware approach to cloud application elasticity

Author(s):  
Andreas Tsagkaropoulos ◽  
Yiannis Verginadis ◽  
Nikos Papageorgiou ◽  
Fotis Paraskevopoulos ◽  
Dimitris Apostolou ◽  
...  
Keyword(s):  
2020 ◽  
Vol 24 (5) ◽  
pp. 45-53
Author(s):  
Gagangeet Singh Aujla ◽  
Masoud Barati ◽  
Omer Rana ◽  
Schahram Dustdar ◽  
Ayman Noor ◽  
...  

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1553
Author(s):  
Marian Rusek ◽  
Grzegorz Dwornicki

Introduction of virtualization containers and container orchestrators fundamentally changed the landscape of cloud application development. Containers provide an ideal way for practical implementation of microservice-based architecture, which allows for repeatable, generic patterns that make the development of reliable, distributed applications more approachable and efficient. Orchestrators allow for shifting the accidental complexity from inside of an application into the automated cloud infrastructure. Existing container orchestrators are centralized systems that schedule containers to the cloud servers only at their startup. In this paper, we propose a swarm-like distributed cloud management system that uses live migration of containers to dynamically reassign application components to the different servers. It is based on the idea of “pheromone” robots. An additional mobile agent process is placed inside each application container to control the migration process. The number of parallel container migrations needed to reach an optimal state of the cloud is obtained using models, experiments, and simulations. We show that in the most common scenarios the proposed swarm-like algorithm performs better than existing systems, and due to its architecture it is also more scalable and resilient to container death. It also adapts to the influx of containers and addition of new servers to the cloud automatically.


2021 ◽  
Vol 1078 (1) ◽  
pp. 012001
Author(s):  
A N Abdul Muta’ali ◽  
N Sazali ◽  
S A C Ghani ◽  
J Walter

Author(s):  
Xiaobin Li ◽  
Chao Yin

Abstract Machine tools (MTs) are the core manufacturing resources for discrete manufacturing enterprises. In the cloud manufacturing environment, MTs are massive, heterogeneous, widely dispersed and highly autonomous, which makes it difficult for cloud manufacturing mode to be deeply applied to support the networked collaboration operation among manufacturing enterprises. Realizing universal access and cloud application of various MTs is an essential prerequisite to solve the above problem. In this paper, an OSGi-based adaptation access method of MTs is proposed. First, the MTs information description model in the cloud manufacturing environment is built. Then, an OSGi-based adaptation access framework of MTs is constructed, and key enabling technologies, including machine tool information acquisition and processing, Bundle and Subsystem construction, are studied. Finally, an application case is conducted to verify the effectiveness and feasibility of the proposed method.


2016 ◽  
Vol 106 (01-02) ◽  
pp. 77-82
Author(s):  
G. Rehage ◽  
F. Isenberg ◽  
R. Reisch ◽  
J. Weber ◽  
B. Jurke ◽  
...  

Auf dem Weg zu Industrie 4.0 wird die Arbeitsvorbereitung zunehmend von kognitiver Informationstechnik unterstützt. Der Beitrag präsentiert die bisherigen Ergebnisse des Forschungsprojekts „Intelligente Arbeitsvorbereitung auf Basis virtueller Werkzeugmaschinen“. Projektziel ist eine Cloud-Dienstleistungsplattform zur Reduzierung der Rüst- und Nebenzeiten durch eine intelligente Planung. Hierzu zählen unter anderem die Auswahl und Validierung alternativer Maschinen sowie die automatische Optimierung der Einrichtungsparameter durch verteilte Simulationen.   On the way to industry 4.0, the operations planning and scheduling will be aided by cognitive information systems. This contribution presents the previous findings of a research project called “Smart operations planning and scheduling on the basis of virtual machine tools” (translated from German). The aim of the project is the development of a cloud service for the smart planning of manufacturing operations; that will reduce the setup and non-productive times of machine tools. This is achieved by the automatic selection of alternative CNC machines, as well as the optimization of setup parameters via distributed simulation.


Sign in / Sign up

Export Citation Format

Share Document