Middleware services for distributed virtual environments

PhD ThesisDistributed Virtual Environments (DVEs) are virtual environments which allow dispersed users to interact with each other and the virtual world through the underlying network. Scalability is a major challenge in building a successful DVE, which is directly affected by the volume of message exchange. Different techniques have been deployed to reduce the volume of message exchange in order to support large numbers of simultaneous participants in a DVE. Interest management is a popular technique for filtering unnecessary message exchange between users. The rationale behind interest management is to resolve the "interests" of users and decide whether messages should be exchanged between them. There are three basic interest management approaches: region-based, aura-based and hybrid approaches. However, if the time taken for an interest management approach to determine interests is greater than the duration of the interaction, it is not possible to guarantee interactions will occur correctly or at all. This is termed the Missed Interaction Problem, which all existing interest management approaches are susceptible to. This thesis provides a new aura-based interest management approach, termed Predictive Interest management (PIM), to alleviate the missed interaction problem. PIM uses an enlarged aura to detect potential aura-intersections and iii initiate message exchange. It utilises variable message exchange frequencies, proportional to the intersection degree of the objects' expanded auras, to restrict bandwidth usage. This thesis provides an experimental system, the PIM system, which couples predictive interest management with the de-centralised server communication model. It utilises the Common Object Request Broker Architecture (CORBA) middleware standard to provide an interoperable middleware for DVEs. Experimental results are provided to demonstrate that PIM provides a scalable interest management approach which alleviates the missed interaction problem

Middleware services for distributed virtual environments

PhD ThesisDistributed Virtual Environments (DVEs) are virtual environments which allow dispersed users to interact with each other and the virtual world through the underlying network. Scalability is a major challenge in building a successful DVE, which is directly affected by the volume of message exchange. Different techniques have been deployed to reduce the volume of message exchange in order to support large numbers of simultaneous participants in a DVE. Interest management is a popular technique for filtering unnecessary message exchange between users. The rationale behind interest management is to resolve the "interests" of users and decide whether messages should be exchanged between them. There are three basic interest management approaches: region-based, aura-based and hybrid approaches. However, if the time taken for an interest management approach to determine interests is greater than the duration of the interaction, it is not possible to guarantee interactions will occur correctly or at all. This is termed the Missed Interaction Problem, which all existing interest management approaches are susceptible to. This thesis provides a new aura-based interest management approach, termed Predictive Interest management (PIM), to alleviate the missed interaction problem. PIM uses an enlarged aura to detect potential aura-intersections and iii initiate message exchange. It utilises variable message exchange frequencies, proportional to the intersection degree of the objects' expanded auras, to restrict bandwidth usage. This thesis provides an experimental system, the PIM system, which couples predictive interest management with the de-centralised server communication model. It utilises the Common Object Request Broker Architecture (CORBA) middleware standard to provide an interoperable middleware for DVEs. Experimental results are provided to demonstrate that PIM provides a scalable interest management approach which alleviates the missed interaction problem

Integration of ROS2 with a simulation environment

Dissertação de mestrado integrado em Engenharia InformáticaCurrently, the University of Minho owns a driving simulator, from now on referred to as Driving Simulator Mockup 2-Wheeler (DSM-2W), which mimics a real driving environment for motorcycles. This simulator can reproduce diverse driving scenarios, like driving on different roads, traffic, and weather conditions, and is mostly used to test how the driver reacts to stimulus from subsystems under test in a particular scenario. The simulator has several components, namely, the Mock-up, which represents the motorcycle physically, the software responsible for the simulation environment, that is also projected on a screen, called SILAB [1] as well as several other subsystems and respective software, which all together form a complex distributed system. SILAB creates realistic graphic environments, has different models to control the behavior of other drivers and pedestrians, generates 3D sounds, and facilitates the personalization of the simulation scenario. Robot Operating System 2 (ROS2) [2] provides a set of tools and software libraries that facilitate the develop ment of robot systems and applications. With the increasing reliance on software, sensors, and actuators in the automotive domain, it makes sense to view cars [3] and motorcycles as robots. Therefore, it also makes sense to use ROS2 in the simulation domain to solve the problems at hand. This dissertation describes how ROS2, a well-known and accepted middleware for robotic applications, can also play a role in these contexts acting as a universal interface between motorcycle simulators and external subsystems and thereby significantly improving the system’s expansibility and those subsystems’ portability and reusability.A Universidade do Minho possui um simulador de motas, denominado Driving Simulator Mockup 2-Wheeler (DSM-2W), que imita um ambiente real de condução de motas. Esta ferramenta consegue reproduzir diversos cenários de condução, como conduzir em diferentes condições de estrada, tráfego, bem como em diferentes condições meteorológicas. Esta ferramenta é sobretudo usada para testar como o condutor reage a estímulos de vários sub-sistemas em teste em cenários particulares. O simulador possui diversos componentes, o Mock-up, que representa a mota fisicamente, o software responsável pela projeção do ambiente de simulação no ecrã, chamado SILAB [1], mais um conjunto de sub-sistemas e o respetivo software, que no conjunto formam um complexo sistema distribuído. O SILAB cria ambientes de simulação realistas, tem diferentes modelos para controlar o comportamento dos outros condutores e dos pedestres, gera sons 3D e facilita a personalização do cenário da simulação. O Robot Operating System 2 (ROS2) possui um conjunto de ferramentas e bibliotecas para desenvolver aplicações para robôs [2]. Com o aumento do uso de software, sensores, e atuadores no contexto automóvel, faz sentido equiparar veículos automóveis [3] e motas a robôs Portanto, também faz sentido usar o ROS2 para resolver problemas neste contexto. O objetivo desta dissertação passa por mostrar como o ROS2, um middleware bastante utilizado em aplicações para robôs, pode ter um papel importante em contextos de simulação ao atuar como uma interface universal entre sub-sistemas a testar e um simulador de motas e consequentemente melhorar a extensibilidade do simulador e a portabilidade e reusabilidade desses sub-sistemas

A Review of Platforms for the Development of Agent Systems

Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.Comment: 40 pages, 2 figures, 9 tables, 83 reference

Survey of context provisioning middleware

In the scope of ubiquitous computing, one of the key issues is the awareness of context, which includes diverse aspects of the user's situation including his activities, physical surroundings, location, emotions and social relations, device and network characteristics and their interaction with each other. This contextual knowledge is typically acquired from physical, virtual or logical sensors. To overcome problems of heterogeneity and hide complexity, a significant number of middleware approaches have been proposed for systematic and coherent access to manifold context parameters. These frameworks deal particularly with context representation, context management and reasoning, i.e. deriving abstract knowledge from raw sensor data. This article surveys not only related work in these three categories but also the required evaluation principles. © 2009-2012 IEEE

Regionally distributed architecture for dynamic e-learning environment (RDADeLE)

e-Learning is becoming an influential role as an economic method and a flexible mode of study in the institutions of higher education today which has a presence in an increasing number of college and university courses. e-Learning as system of systems is a dynamic and scalable environment. Within this environment, e-learning is still searching for a permanent, comfortable and serviceable position that is to be controlled, managed, flexible, accessible and continually up-to-date with the wider university structure. As most academic and business institutions and training centres around the world have adopted the e-learning concept and technology in order to create, deliver and manage their learning materials through the web, it has become the focus of investigation. However, management, monitoring and collaboration between these institutions and centres are limited. Existing technologies such as grid, web services and agents are promising better results. In this research a new architecture has been developed and adopted to make the e-learning environment more dynamic and scalable by dividing it into regional data grids which are managed and monitored by agents. Multi-agent technology has been applied to integrate each regional data grid with others in order to produce an architecture which is more scalable, reliable, and efficient. The result we refer to as Regionally Distributed Architecture for Dynamic e-Learning Environment (RDADeLE). Our RDADeLE architecture is an agent-based grid environment which is composed of components such as learners, staff, nodes, regional grids, grid services and Learning Objects (LOs). These components are built and organised as a multi-agent system (MAS) using the Java Agent Development (JADE) platform. The main role of the agents in our architecture is to control and monitor grid components in order to build an adaptable, extensible, and flexible grid-based e-learning system. Two techniques have been developed and adopted in the architecture to build LOs' information and grid services. The first technique is the XML-based Registries Technique (XRT). In this technique LOs' information is built using XML registries to be discovered by the learners. The registries are written in Dublin Core Metadata Initiative (DCMI) format. The second technique is the Registered-based Services Technique (RST). In this technique the services are grid services which are built using agents. The services are registered with the Directory Facilitator (DF) of a JADE platform in order to be discovered by all other components. All components of the RDADeLE system, including grid service, are built as a multi-agent system (MAS). Each regional grid in the first technique has only its own registry, whereas in the second technique the grid services of all regional grids have to be registered with the DF. We have evaluated the RDADeLE system guided by both techniques by building a simulation of the prototype. The prototype has a main interface which consists of the name of the system (RDADeLE) and a specification table which includes Number of Regional Grids, Number of Nodes, Maximum Number of Learners connected to each node, and Number of Grid Services to be filled by the administrator of the RDADeLE system in order to create the prototype. Using the RST technique shows that the RDADeLE system can be built with more regional grids with less memory consumption. Moreover, using the RST technique shows that more grid services can be registered in the RDADeLE system with a lower average search time and the search performance is increased compared with the XRT technique. Finally, using one or both techniques, the XRT or the RST, in the prototype does not affect the reliability of the RDADeLE system.Royal Commission for Jubail and Yanbu - Directorate General For Jubail Project Kingdom of Saudi Arabi