Using Clouds to Scale Grid Resources: An Economic Model

Infrastructure as a Service clouds are a flexible and fast way to obtain (virtual) resources as demand varies. Grids, on the other hand, are middleware platforms able to combine resources from different administrative domains for task execution. Clouds can be used by grids as providers of devices such as virtual machines, so they only use the resources they need. But this requires grids to be able to decide when to allocate and release those resources. Here we introduce and analyze by simulations an economic mechanism (a) to set resource prices and (b) resolve when to scale resources depending on the users’ demand. This system has a strong emphasis on fairness, so no user hinders the execution of other users’ tasks by getting too many resources. Our simulator is based on the well-known GridSim software for grid simulation, which we expand to simulate infrastructure clouds. The results show how the proposed system can successfully adapt the amount of allocated resources to the demand, while at the same time ensuring that resources are fairly shared among users.

Videoconference capacity Leasing on Hybrid Clouds.

This paper proposes a new methodology focused on implementing cost effective architectures on Cloud Computing systems. With this methodology the paper presents some disadvantages of systems that are based on single Cloud architectures and gives some advices for taking into account in the development of hybrid systems. The work also includes a validation of these ideas implemented in a complete videoconference service developed with our research group. This service allows a great number of users per conference, multiple simultaneous conferences, different client software (requiring transcodification of audio and video flows) and provides a service like automatic recording. Furthermore it offers different kinds of connectivity including SIP clients and a client based on Web 2.0. The ideas proposed in this article are intended to be a useful resource for any researcher or developer who wants to implement cost effective systems on several Clouds

Validation of real time dispersion of Tritium clouds over the Western Mediterranean Basin in different assesments

Real time Tritium concentrations in air coming from an ITER-like reactor as source were coupled the European Centre Medium Range Weather Forecast (ECMWF) numerical model with the lagrangian atmospheric dispersion model FLEXPART. This tool ECMWF/FLEXPART was analyzed in normal operating conditions in the Western Mediterranean Basin during 45 days at summer 2010. From comparison with NORMTRI plumes over Western Mediterranean Basin the real time results have demonstrated an overestimation of the corresponding climatologically sequence Tritium concentrations in air outputs, at several distances from the reactor. For these purpose two clouds development patterns were established. The first one was following a cyclonic circulation over the Mediterranean Sea and the second one was based in the cloud delivered over the Interior of the Iberian Peninsula by another stabilized circulation corresponding to a High. One of the important remaining activities defined then, was the tool qualification. The aim of this paper is to present the ECMWF/FLEXPART products confronted with Tritium concentration in air data. For this purpose a database to develop and validate ECMWF/FLEXPART tritium in both assessments has been selected from a NORMTRI run. Similarities and differences, underestimation and overestimation with NORMTRI will allowfor refinement in some features of ECMWF/FLEXPART

A semantic scheduler architecture for federated hybrid clouds

Cloud computing is one the most relevant computing paradigms available nowadays. Its adoption has increased during last years due to the large investment and research from business enterprises and academia institutions. Among all the services cloud providers usually offer, Infrastructure as a Service has reached its momentum for solving HPC problems in a more dynamic way without the need of expensive investments. The integration of a large number of providers is a major goal as it enables the improvement of the quality of the selected resources in terms of pricing, speed, redundancy, etc. In this paper, we propose a system architecture, based on semantic solutions, to build an interoperable scheduler for federated clouds that works with several IaaS (Infrastructure as a Service) providers in a uniform way. Based on this architecture we implement a proof-of-concept prototype and test it with two different cloud solutions to provide some experimental results about the viability of our approach.

Tritium clouds environmental impact in air into the Western Mediterranean Basin evaluation

The paper considers short-term releases of tritium (mainly but not only tritium hydride (HT)) to the atmosphere from a potential ITER-like fusion reactor located in the Mediterranean Basin and explores if the short range legal exposure limits are exceeded (both locally and downwind). For this, a coupled Lagrangian ECMWF/FLEXPART model has been used to follow real time releases of tritium. This tool was analyzed for nominal tritium operational conditions under selected incidental conditions to determine resultant local and Western Mediterranean effects, together with hourly observations of wind, to provide a short-range approximation of tritium cloud behavior. Since our results cannot be compared with radiological station measurements of tritium in air, we use the NORMTRI Gaussian model. We demonstrate an overestimation of the sequence of tritium concentrations in the atmosphere, close to the reactor, estimated with this model when compared with ECMWF/FLEXPART results. A Gaussian “mesoscale” qualification tool has been used to validate the ECMWF/FLEXPART for winter 2010/spring 2011 with a database of the HT plumes. It is considered that NORMTRI allows evaluation of tritium-in-air-plume patterns and its contribution to doses.

A cost-effective methodology applied to videoconference services over hybrid clouds

This paper tackles the optimization of applications in multi-provider hybrid cloud scenarios from an economic point of view. In these scenarios the great majority of solutions offer the automatic allocation of resources on different cloud providers based on their current prices. However our approach is intended to introduce a novel solution by making maximum use of divide and rule. This paper describes a methodology to create cost aware cloud applications that can be broken down into the three most important components in cloud infrastructures: computation, network and storage. A real videoconference system has been modified in order to evaluate this idea with both theoretical and empirical experiments. This system has become a widely used tool in several national and European projects for e-learning and collaboration purposes.

Development of a management system for virtual machines on private clouds

Cloud computing and, more particularly, private IaaS, is seen as a mature technol- ogy with a myriad solutions to choose from. However, this disparity of solutions and products has instilled in potential adopters the fear of vendor and data lock- in. Several competing and incompatible interfaces and management styles have increased even more these fears. On top of this, cloud users might want to work with several solutions at the same time, an integration that is difficult to achieve in practice. In this Master Thesis I propose a management architecture that tries to solve these problems; it provides a generalized control mechanism for several cloud infrastructures, and an interface that can meet the requirements of the users. This management architecture is designed in a modular way, and using a generic infor- mation model. I have validated the approach through the implementation of the components needed for this architecture to support a sample private IaaS solution: OpenStack.

Deciduous tree reconstruction algorithm based on cylinder fitting from mobile terrestrial laser scanned point clouds

Vector reconstruction of objects from an unstructured point cloud obtained with a LiDAR-based system (light detection and ranging) is one of the most promising methods to build three dimensional models of orchards. The cylinder fitting method for woody structure reconstruction of leafless trees from point clouds obtained with a mobile terrestrial laser scanner (MTLS) has been analysed. The advantage of this method is that it performs reconstruction in a single step. The most time consuming part of the algorithm is generation of the cylinder direction, which must be recalculated at the inclusion of each point in the cylinder. The tree skeleton is obtained at the same time as the cluster of cylinders is formed. The method does not guarantee a unique convergence and the reconstruction parameter values must be carefully chosen. A balanced processing of clusters has also been defined which has proven to be very efficient in terms of processing time by following the hierarchy of branches, predecessors and successors. The algorithm was applied to simulated MTLS of virtual orchard models and to MTLS data of real orchards. The constraints applied in the method have been reviewed to ensure better convergence and simpler use of parameters. The results obtained show a correct reconstruction of the woody structure of the trees and the algorithm runs in linear logarithmic time

3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds

3D crop reconstruction with a high temporal resolution and by the use of non-destructive measuring technologies can support the automation of plant phenotyping processes. Thereby, the availability of such 3D data can give valuable information about the plant development and the interaction of the plant genotype with the environment. This article presents a new methodology for georeferenced 3D reconstruction of maize plant structure. For this purpose a total station, an IMU, and several 2D LiDARs with different orientations were mounted on an autonomous vehicle. By the multistep methodology presented, based on the application of the ICP algorithm for point cloud fusion, it was possible to perform the georeferenced point clouds overlapping. The overlapping point cloud algorithm showed that the aerial points (corresponding mainly to plant parts) were reduced to 1.5%–9% of the total registered data. The remaining were redundant or ground points. Through the inclusion of different LiDAR point of views of the scene, a more realistic representation of the surrounding is obtained by the incorporation of new useful information but also of noise. The use of georeferenced 3D maize plant reconstruction at different growth stages, combined with the total station accuracy could be highly useful when performing precision agriculture at the crop plant level.