A GRID-BASED E-LEARNING MODEL FOR OPEN UNIVERSITIES

E-learning has grown to become a widely accepted method of learning all over the world. As a result, many e-learning platforms which have been developed based on varying technologies were faced with some limitations ranging from storage capability, computing power, to availability or access to the learning support infrastructures. This has brought about the need to develop ways to effectively manage and share the limited resources available in the e-learning platform. Grid computing technology has the capability to enhance the quality of pedagogy on the e-learning platform. In this paper we propose a Grid-based e-learning model for Open Universities. An attribute of such universities is the setting up of multiple remotely located campuses within a country. The grid-based e-learning model presented in this work possesses the attributes of an elegant architectural framework that will facilitate efficient use of available e-learning resources and cost reduction, leading to general improvement of the overall quality of the operations of open universities

Diseño e implementación de una arquitectura grid de recursos para el sector educativo en la Universidad Autónoma de Bucaramanga, como parte del macroproyecto Grid Colombia.

En el siguiente documento, se recopila información sobre cada uno de los temas que conciernen al diseño, instalación y puesta a punto de los diferentes elementos que intervienen en una arquitectura GRID. Se describe el proceso de diseño e implementación de una arquitectura GRID de recursos, se plantean las posibles fases que se deben llevar a cabo así como las actividades a desarrollar en cada una de ellas. Se describe de forma detallada cada una de las pruebas y conexiones ejecutadas sobre el sistema GRID de la Universidad Autónoma de Bucaramanga y sus resultados

Distributed k-ary System: Algorithms for Distributed Hash Tables

This dissertation presents algorithms for data structures called distributed hash tables (DHT) or structured overlay networks, which are used to build scalable self-managing distributed systems. The provided algorithms guarantee lookup consistency in the presence of dynamism: they guarantee consistent lookup results in the presence of nodes joining and leaving. Similarly, the algorithms guarantee that routing never fails while nodes join and leave. Previous algorithms for lookup consistency either suffer from starvation, do not work in the presence of failures, or lack proof of correctness. Several group communication algorithms for structured overlay networks are presented. We provide an overlay broadcast algorithm, which unlike previous algorithms avoids redundant messages, reaching all nodes in O(log n) time, while using O(n) messages, where n is the number of nodes in the system. The broadcast algorithm is used to build overlay multicast. We introduce bulk operation, which enables a node to efficiently make multiple lookups or send a message to all nodes in a specified set of identifiers. The algorithm ensures that all specified nodes are reached in O(log n) time, sending maximum O(log n) messages per node, regardless of the input size of the bulk operation. Moreover, the algorithm avoids sending redundant messages. Previous approaches required multiple lookups, which consume more messages and can render the initiator a bottleneck. Our algorithms are used in DHT-based storage systems, where nodes can do thousands of lookups to fetch large files. We use the bulk operation algorithm to construct a pseudo-reliable broadcast algorithm. Bulk operations can also be used to implement efficient range queries. Finally, we describe a novel way to place replicas in a DHT, called symmetric replication, that enables parallel recursive lookups. Parallel lookups are known to reduce latencies. However, costly iterative lookups have previously been used to do parallel lookups. Moreover, joins or leaves only require exchanging O(1) messages, while other schemes require at least log(f) messages for a replication degree of f. The algorithms have been implemented in a middleware called the Distributed k-ary System (DKS), which is briefly described

Orchestrating the Dynamic Adaptation of Distributed Software with Process Technology

Software systems are becoming increasingly complex to develop, understand, analyze, validate, deploy, configure, manage and maintain. Much of that complexity is related to ensuring adequate quality levels to services provided by software systems after they are deployed in the field, in particular when those systems are built from and operated as a mix of proprietary and non-proprietary components. That translates to increasing costs and difficulties when trying to operate large-scale distributed software ensembles in a way that continuously guarantees satisfactory levels of service. A solution can be to exert some form of dynamic adaptation upon running software systems: dynamic adaptation can be defined as a set of automated and coordinated actions that aim at modifying the structure, behavior and performance of a target software system, at run time and without service interruption, typically in response to the occurrence of some condition(s). To achieve dynamic adaptation upon a given target software system, a set of capabilities, including monitoring, diagnostics, decision, actuation and coordination, must be put in place. This research addresses the automation of decision and coordination in the context of an end-to-end and externalized approach to dynamic adaptation, which allows to address as its targets legacy and component-based systems, as well as new systems developed from scratch. In this approach, adaptation provisions are superimposed by a separate software platform, which operates from the outside of and orthogonally to the target application as a whole; furthermore, a single adaptation possibly spans concerted interventions on a multiplicity of target components. To properly orchestrate those interventions, decentralized process technology is employed for describing, activating and coordinating the work of a cohort of software actuators, towards the intended end-to-end dynamic adaptation. The approach outlined above, has been implemented in a prototype, code-named Workflakes, within the Kinesthetics eXtreme project investigating externalized dynamic adaptation, carried out by the Programming Systems Laboratory of Columbia University, and has been employed in a set of diverse case studies. This dissertation discusses and evaluates the concept of process-based orchestration of dynamic adaptation and the Workflakes prototype on the basis of the results of those case studies

Modelling grid architecture.

This thesis evaluates software engineering methods, especially event modelling of distributed systems architecture, by applying them to specific data-grid projects. Other methods evaluated include requirements' analysis, formal architectural definition and discrete event simulation. A novel technique for matching architectural styles to requirements is introduced. Data-grids are a new class of networked information systems arising from e-science, itself an emergent method for computer-based collaborative research in the physical sciences. The tools used in general grid systems, which federate distributed resources, are reviewed, showing that they do not clearly guide architecture. The data-grid projects, which join heterogeneous data stores specifically, put required qualities at risk. Such risk of failure is mitigated in the EGSO and AstroGrid solar physics data-grid projects' designs by modelling. Design errors are trapped by rapidly encoding and evaluating informal concepts, architecture, component interaction and objects. The success of software engineering modelling techniques depends on the models' accuracy, ability to demonstrate the required properties, and clarity (so project managers and developers can act on findings). The novel formal event modelling language chosen, FSP, meets these criteria at the diverse early lifecycle stages (unlike some techniques trialled). Models permit very early testing, finding hidden complexity, gaps in designed protocols and risks of unreliability. However, simulation is shown to be more suitable for evaluating qualities like scalability, which emerge when there are many component instances. Design patterns (which may be reused in other data-grids to resolve commonly encountered challenges) are exposed in these models. A method for generating useful models rapidly, introducing the strength of iterative lifecycles to sequential projects, also arises. Despite reported resistance to innovation in industry, the software engineering techniques demonstrated may benefit commercial information systems too