A Jacobi-based algorithm for computing symmetric eigenvalues and eigenvectors in a two-dimensional mesh

The paper proposes an algorithm for computing symmetric eigenvalues and eigenvectors that uses a one-sided Jacobi approach and is targeted to a multicomputer in which nodes can be arranged as a two-dimensional mesh with an arbitrary number of rows and columns. The algorithm is analysed through simple analytical models of execution time, which show that an adequate choice of the mesh configuration (number of rows and columns) can improve performance significantly, with respect to a one-dimensional configuration, which is the most frequently considered scenario in current proposals. This improvement is especially noticeable in large systems.Peer ReviewedPostprint (published version

A methodology for user-oriented scalability analysis

Scalability analysis provides information about the effectiveness of increasing the number of resources of a parallel system. Several methods have been proposed which use different approaches to provide this information. This paper presents a family of analysis methods oriented to the user. The methods in this family should assist the user in estimating the benefits when increasing the system size. The key issue in the proposal is the appropriate combination of a scaling model, which reflects the way the users utilize an increasing number of resources, and a figure of merit that the user wants to improve with the larger system. Another important element in the proposal is the approach to characterize the scalability, which enables quick visual analyses and comparisons. Finally, three concrete examples of methods belonging to the proposed family are introduced in this paper.Peer ReviewedPostprint (published version

The Fifth International Conference on Intelligent Environments (IE 09): a report

The development of intelligent environments is considered an important step towards the realization of the ambient intelligence vision. Intelligent environments are technologically augmented everyday spaces, which intuitively support human activity. The IE conferences traditionally provide a leading edge forum for researchers and engineers to present their latest research and to discuss future directions in the area of intelligent environments. This article briefly presents the content of the Fifth International Conference on Intelligent Environments (IE09), which was held July 20–21 at the Castelldefels campus, of the Technical University of Catalonia, near Barcelona, Spain.Postprint (published version

Sortir del Laberint : un joc per pensar

“Sortir del Laberint” és un joc tipus puzzle, l’objectiu principal del qual és aconseguir que el jugador pugui sortir d’un laberint amb el mínim nombre de passes i el més ràpid possible.Preprin

OLSRp: predicting control information to achieve scalability in OLSR ad hoc networks

Scalability is a key design challenge that routing protocols for ad hoc networks must properly address to maintain the network performance when the number of nodes increases. We focus on this issue by reducing the amount of control information messages that a link state proactive routing algorithm introduces to the network. Our proposal is based on the observation that a high percentage of those messages is always the same. Therefore, we introduce a new mechanism that can predict the control messages that nodes need for building an accurate map of the network topology so they can avoid resending the same messages. This prediction mechanism, applied to OLSR protocol, could be used to reduce the number of messages transmitted through the network and to save computational processing and energy consumption. Our proposal is independent of the OLSR configuration parameters and it can dynamically self-adapt to network changes.Postprint (published version

Group Prediction in Collaborative Learning

We propose an approach for predicting group formations, to address the problem of automating the incorporation of group awareness into CSCL applications. Contextual information can enable the construction of applications that effectively assist the group members to automatically communicate in synchronous and collocated collaborative learning activities. We used data traces collected from the study of students’ behavior to train and test an intelligent system. Results have shown that context-information can be effectively used as a basis for a middleware for a dynamic group management. Inferring group membership is technically viable and can be used in real world settings.Postprint (published version

Active yellow pages: a pipelined resource management architecture for wide-area network computing

This paper describes a novel, pipelined resource management architecture for computational grids. The design is based on two key realizations. One is that resource management involves a sequence of tasks that is best handled by a pipeline. As shown in the paper, this approach results, in a scalable architecture for decentralized scheduling. The other realization is that static aggregation of resources for improved scheduling is inadequate in wide-area computing environments because the needs of users and jobs change with both, location and time. The described architecture addresses this problem by dynamically aggregating resources in a manner that continuously optimizes system response. This is accomplished by way of an active yellow pages directory that allows aggregation constraints to be (re)defined on the fly. An initial prototype of the active yellow pages service has been deployed in the PUNCH network computing environment. Experiences with the production PUNCH system and preliminary results from controlled experiments indicate that the active yellow pages service performs well.Peer Reviewe

Mobile Autonomous Sensing Unit (MASU): a framework that supports distributed pervasive data sensing

Pervasive data sensing is a major issue that transverses various research areas and application domains. It allows identifying people’s behaviour and patterns without overwhelming the monitored persons. Although there are many pervasive data sensing applications, they are typically focused on addressing specific problems in a single application domain, making them difficult to generalize or reuse. On the other hand, the platforms for supporting pervasive data sensing impose restrictions to the devices and operational environments that make them unsuitable for monitoring loosely-coupled or fully distributed work. In order to help address this challenge this paper present a framework that supports distributed pervasive data sensing in a generic way. Developers can use this framework to facilitate the implementations of their applications, thus reducing complexity and effort in such an activity. The framework was evaluated using simulations and also through an empirical test, and the obtained results indicate that it is useful to support such a sensing activity in loosely-coupled or fully distributed work scenarios.Peer ReviewedPostprint (published version

OIoT: a platform to manage opportunistic IoT communities

Opportunistic Internet of Things (IoT) extends the concept of opportunistic networking combining human users carrying mobile devices and smart things. It explores the relationships between humans and the opportunistic connection of smart objects. This paper presents a software infrastructure, named Opportunistic IoT Platform (OIoT), which helps developers to create and manage opportunistic IoT communities between smart devices. The platform enables the creation of opportunistic IoT communities that support the AllJoyn communications framework, for IoT devices and applications. Results from a preliminary evaluation of the OIoT platform indicate that this infrastructure is useful to manage and share data across opportunistic IoT communities.Peer ReviewedPostprint (published version

Supporting context-aware collaborative learning through automatic group formation

Collaborative learning is based on groups of students working together with traditional and computer-based tools or applications. We have found that to make these supporting applications more effective we need to address the problem of automating group awareness in CSCL applications by estimating group arrangements from location sensors and the history of interaction. This contextual information can enable the construction of applications that facilitate communication among group members in synchronous and collocated collaborative learning activities. We used data traces collected from the study of students‟ behavior to train and test an intelligent system. Results show that context-information can be effectively used as a basis for a middleware for automating group management. Inferring group membership is technically feasible, can be integrated in group-support applications and can be used in real-world settings.Postprint (published version