Distributed environment for efficient virtual machine image management in federated Cloud architectures

Kimovski, Dragi; Marosi, Attila Csaba; Gec, Sandi; Saurabh, Nishant; Kertész, Attila; Kecskeméti, Gábor; Stankovski, Vlado; Prodan, Radu

doi:10.1002/cpe.4220

Cited by 5 publications

(3 citation statements)

References 15 publications

(24 reference statements)

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“…The ENTICE project [19,11] is a multidisciplinary team of computer scientists, application developers, cloud providers and operators with the aim to research a ubiquitous repository-based technology for VMI (and container) management called ENTICE environment. This environment proves a universal backbone for IaaS image management operations, which accommodate the needs for different use cases with dynamic resource (e.g., requiring resources for minutes or just for a few seconds) and other Quality of Service (QoS) requirements.…”

Section: The Entice Projectmentioning

confidence: 99%

ENTICE VM Image Analysis and Optimised Fragmentation

et al. 2018

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Section: The Entice Projectmentioning

confidence: 99%

ENTICE VM Image Analysis and Optimised Fragmentation

et al. 2018

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“…Razavi and Kielmann proposed an elastic VM deployment mechanism using VMI caches to overcome the VM start‐up bottlenecks. Kimovski et al described mechanisms how to efficient manage virtual machines in federated cloud repositories.…”

Section: Related Workmentioning

confidence: 99%

Semantic approach for multi‐objective optimisation of the ENTICE distributed Virtual Machine and container images repository

Gec

Kimovski

Paščinski

et al. 2017

Concurrency and Computation

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New software engineering technologies facilitate development of applications from reusable software components, such as Virtual Machine and container images (VMI/CIs). Key requirements for the storage of VMI/CIs in public or private repositories are their fast delivery and cloud deployment times. ENTICE is a federated storage facility for VMI/CIs that provides optimisation mechanisms through the use of fragmentation and replication of images and a Pareto Multi-Objective Optimisation (MO) solver. The operation of the MO solver is, however, time-consuming due to the size and complexity of the metadata, * Vlado Stankovski, University of Ljubljana, Faculty of Civil and Geodetic Engineering, Jamova cesta 2, SI-1000 Ljubljana, Slovenia.2 E-mail: vlado.stankovski@fgg.uni-lj.si 1 specifying various non-functional requirements for the management of VMI/CIs, such as geolocation, operational cost and delivery time. In this work, we address this problem with a new semantic approach, which uses an ontology of the federated ENTICE repository, knowledge base and constraint-based reasoning mechanism. Open Source technologies such as Protégé, Jena Fuseki and Pellet were used to develop a solution. Two specific use cases: (1) repository optimisation with offline and (2) online redistribution of VMI/CIs, are presented in detail. In both use cases, data from the knowledge base is provided to the MO solver. It is shown that Pellet based reasoning can be used to reduce the input metadata size used in the optimisation process by taking into consideration the geographic location of the VMI/CIs and the provenance of the VMI fragments. It is shown that this process leads to reduction of the input metadata size for the MO solver by up to 60% and reduction of the total optimization time of the MO solver by up to 68%, while fully preserving the quality of the solution, which is significant.

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“…In the paper Distributed environment for efficient virtual machine image management in federated Cloud architectures , a set of novel approaches for the efficient management of distributed virtual machine image (VMI) repositories in federated Cloud environments, is presented. The paper presents a set of tools to simplify the creation of lightweight and highly optimized VMIs tuned for specific application requirements.…”

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Large Scale Cooperative Virtual Environments

Ricci

Iosup

Prodan

2018

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The recent advances in networking have determined an increasing use of information technology to support interactive networked cooperative applications. Several novel applications have emerged in this area: social networks, distributed virtual environments (DVEs), collaborative learning systems, large-scale crowd-based applications, and mobile collaborative platforms. This kind of applications can be generally referred as Large ScaleCooperative Virtual Environments. The definition of these applications requires affording several challenges such as the design of user interfaces, coordination protocols, mobility models, and proper middleware and architectures supporting distributed cooperation. Collaborative applications may greatly benefit from the support of different kinds of platforms, both cloud and peer to peer and also platforms recently proposed for the Internet of things (IoT) like fog computing. Integration of different platforms, for instance, mobile and cloud environments, is currently a challenge.Furthermore, the analysis and validation of the huge amount of content generated by these applications asks for proper data analysis and processing techniques. The special issue's aim is to investigate open challenges for such applications, related to both the applications' design and the definition of proper architectures. Some important challenges are, for instance, collaborative protocols design, large-scale processing of user information, privacy and security issues, state consistency/persistence, and efficient support definition.This special includes six high-quality papers, five of them are extended versions of the papers accepted and presented at the 4th Workshop on Large Scale Distributed Virtual Environments on Clouds and P2P held in conjunction with Euro-Par 2016 in Grenoble, France, in August 2016. In the following, we give a brief description of each paper.De Salve et al in the paper Predicting the availability of users devices in decentralized online social networks 1 investigate whether availability patterns of users in online social networks (OSNs) can be predicted. The paper proposes a flexible linear predictor whose goal is to estimate the future availability of a user (ie, online or offline) by taking into account only the availability history of that user. The information returned by the predictor is useful to support information allocation/diffusion in distributed OSNs (DOSNs). The predictor may be configured by setting a set of parameters like the size of the period of time in the future to predict and the size of the elapsed period of time exploited for the prediction. Furthermore, the paper proposes several selection strategies to choose users more likely to be online in a time interval. These strategies can be exploited to select the peers which host data replica in a DOSN.The paper Efficient and scalable execution of smart city parallel applications 2 presents an analysis and prediction of internet traffic generated by vehicle and pedestrian devices moving across a "smart avenue". The...

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Distributed environment for efficient virtual machine image management in federated Cloud architectures

Cited by 5 publications

References 15 publications

ENTICE VM Image Analysis and Optimised Fragmentation

ENTICE VM Image Analysis and Optimised Fragmentation

Semantic approach for multi‐objective optimisation of the ENTICE distributed Virtual Machine and container images repository

Large Scale Cooperative Virtual Environments

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