Frincu M.E.,Research Institute E Austria |
Frincu M.E.,West University of Timisoara
Future Generation Computer Systems | Year: 2014
Cloud computing is becoming a popular solution for storing data and executing applications due to its on-demand pay-per-use policy that allows access to virtually unlimited resources. In this frame applications such as those oriented towards Web 2.0 begin to be migrated on cloud systems. Web 2.0 applications are usually composed of several components that run indefinitely and need to be available to end users throughout their execution life cycle. Their availability strongly depends on the number of resource failures and on the variation in user hit rate. These problems are usually solved through scaling. A scaled application can span its components on several nodes. Hence if one or more nodes fail it could become unavailable. Therefore we require a method of ensuring the application's functionality despite the number of node failures. In this paper we propose to build highly available applications, i.e., systems with low downtimes, by taking advantage of the component based architecture and of the application scaling property. We present a solution to finding the optimal number of component types needed on nodes so that every type is present on every allocated node. Furthermore nodes cannot exceed a maximum threshold and the total running cost of the applications needs to be minimized. A sub-optimal solution is also given. Both solutions rely on genetic algorithms to achieve their goals. The efficiency of the sub-optimal algorithm is studied with respect to its success rate, i.e., probability of the schedule to provide highly available applications in case all but one node fail. Tests performed on the sub-optimal algorithm in terms of node load, closeness to the optimal solution and success rate prove the algorithm's efficiency.©2013 Published by Elsevier Ltd. All rights reserved.
Mindruta C.,West University of Timisoara |
Fortis T.-F.,West University of Timisoara |
Fortis T.-F.,Research Institute E Austria
Proceedings - 27th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2013 | Year: 2013
In the context of the efforts to organize the knowledge in the new and emerging area of Cloud Computing we performed an analysis of relevant existing developments and built on this basis a framework for a semantic registry of cloud services. The framework contains core ontological definitions and extension mechanisms used to define ontologies for cloud services, related to the aspects of semantic discovery and composition of cloud services. The relevance of the proposed registry can be assessed in relation with cloud interoperability, cloud service composition, as well as software services that offer support for finding and selecting cloud services and for marketing advantages of different cloud providers. © 2013 IEEE.
Sandru C.,Research Institute E Austria |
Venticinque S.,The Second University of Naples
Studies in Computational Intelligence | Year: 2013
The process of developing, deploying and executing cloud applications is greatly influenced by the specifics of the cloud providers regarding the cloud infrastructure and the cloud resources. Important challenges are related to agreeing with the cloud vendors about the application resources and the quality of the services. Migrating the application from one cloud provider to another cloud provider or even using multiple providers at once is also difficult to achieve. The present paper proposes an architectural solution for the above mentioned problems by considering the agency paradigm and a special set of agents called Vendor Agents abstracting the cloud provider differences.
Amato A.,The Second University of Naples |
Tasquier L.,The Second University of Naples |
Copie A.,Research Institute E Austria
Studies in Computational Intelligence | Year: 2013
Elastic provisioning of Cloud resources at IAAS is a mandatory facility to deploy applications on computing elements which are dynamically allocated based on the application needs. Because of the increasing offer of the Cloud market, the effectiveness of provisioning can be increased by selecting and exploiting the best proposal that is compliant with the user's requirements. Due to the current lack of standards and to the heterogeneity of technologies interoperability at IAAS, it is the main issue to be addressed. We propose an agent based solution to abstract IAAS services for negotiation and management of Cloud resources. The paper presents our agent abstraction and its implementation to support two well known Cloud technologies: Open Nebula and Amazon.
Frincu M.E.,West University of Timisoara |
Craciun C.,Research Institute E Austria
Proceedings - 2011 4th IEEE International Conference on Utility and Cloud Computing, UCC 2011 | Year: 2011
As the popularity of cloud computing increases, more and more applications are migrated onto them. Web 2.0 applications are the most common example of such applications. These applications require to scale, be highly available, fault tolerant and able to run uninterrupted for long periods of time (or even indefinitely). Moreover as new cloud providers appear there is a natural tendency towards choosing the best provider or a combination of them for deploying the application. Thus multi-cloud scenarios emerge from this situation. However, as multi-cloud resource provisioning is both complex and costly, the choice of which resources to lend and how to allocate them to application components needs to rely on efficient strategies. These need to take into account many factors including deployment and run-time cost, resource load, and application availability in case of failures. For this aim multi-objective scheduling algorithms seem an appropriate choice. This paper presents an algorithm which tries to achieve application high-availability and fault-tolerance while reducing the application cost and keeping the resource load maximized. The proposed algorithm is compared with a classic Round Robin strategy - used by many commercial clouds - and the obtained results prove the efficiency of our solution. © 2011 IEEE.