Maximising concurrency and scalability in a consistent, causal, distributed virtual reality system, whilst minimising the effect of network delays

The development of large scale virtual reality and simulation systems have been mostly driven by the DIS and HLA standards community. A number of issues are coming to light about the applicability of these standards, in their present state, to the support of general multi-user VR systems. This paper pinpoints four issues that must be readdressed before large scale virtual reality systems become accessible to a larger commercial and public domain: a reduction in the effects of network delays; scalable causal event delivery; update control; and scalable reliable communication. Each of these issues is tackled through a common theme of combining wall clock and causal time-related entity behaviour, knowledge of network delays and prediction of entity behaviour, that together overcome many of the effects of network delay.

Maximising concurrency and scalability in a consistent, causal, distributed virtual reality system, whilst minimising the effect of network delays

The development of large scale virtual reality and simulation systems have been mostly driven by the DIS and HLA standards community. A number of issues are coming to light about the applicability of these standards, in their present state, to the support of general multi-user VR systems. This paper pinpoints four issues that must be readdressed before large scale virtual reality systems become accessible to a larger commercial and public domain: a reduction in the effects of network delays; scalable causal event delivery; update control; and scalable reliable communication. Each of these issues is tackled through a common theme of combining wall clock and causal time-related entity behaviour, knowledge of network delays and prediction of entity behaviour, that together overcome many of the effects of network delays.

Deep Convective System Evolution over Africa and the Tropical Atlantic

In the tropical African and neighboring Atlantic region there is a strong contrast in the properties of deep convection between land and ocean. Here, satellite radar observations are used to produce a composite picture of the life cycle of convection in these two regions. Estimates of the broadband thermal flux from the geostationary Meteosat-8 satellite are used to identify and track organized convective systems over their life cycle. The evolution of the system size and vertical extent are used to define five life cycle stages (warm and cold developing, mature, cold and warm dissipating), providing the basis for the composite analysis of the system evolution. The tracked systems are matched to overpasses of the Tropical Rainfall Measuring Mission satellite, and a composite picture of the evolution of various radar and lightning characteristics is built up. The results suggest a fundamental difference in the convective life cycle between land and ocean. African storms evolve from convectively active systems with frequent lightning in their developing stages to more stratiform conditions as they dissipate. Over the Atlantic, the convective fraction remains essentially constant into the dissipating stages, and lightning occurrence peaks late in the life cycle. This behavior is consistent with differences in convective sustainability in land and ocean regions as proposed in previous studies. The area expansion rate during the developing stages of convection is used to provide an estimate of the intensity of convection. Reasonable correlations are found between this index and the convective system lifetime, size, and depth.

Simulating metals and mine discharges in river basins using a new integrated catchment model for metals: pollution impacts and restoration strategies in the Aries-Mures river system in Transylvania, Romania

The INtegrated CAtchment (INCA) model has been developed to simulate the impact of mine discharges on river systems. The model accounts for the key kinetic chemical processes operating as well as the dilution, mixing and redistribution of pollutants in rivers downstream of mine discharges or acid rock drainage sites. The model is dynamic and simulates the day-to-day behaviour of hydrology and eight metals (cadmium, mercury, copper, zinc, lead, arsenic, manganese and chromium) as well as cyanide and ammonia. The model is semi-distributed and can simulate catchments, sub-catchment and in-stream river behaviour. The model has been applied to the Roia Montan Mine in Transylvania, Romania, and used to assess the impacts of old mine adits on the local catchments as well as on the downstream Aries and Mures river system. The question of mine restoration is investigated and a set of clean-up scenarios investigated. It is shown that the planned restoration will generate a much improved water quality from the mine and also alleviate the metal pollution of the river system.

Development and illustrative outputs of the Community Integrated Assessment System (CIAS), a multi-institutional modular integrated assessment approach for modelling climate change.

This paper describes the development and first results of the “Community Integrated Assessment System” (CIAS), a unique multi-institutional modular and flexible integrated assessment system for modelling climate change. Key to this development is the supporting software infrastructure, SoftIAM. Through it, CIAS is distributed between the community of institutions which has each contributed modules to the CIAS system. At the heart of SoftIAM is the Bespoke Framework Generator (BFG) which enables flexibility in the assembly and composition of individual modules from a pool to form coupled models within CIAS, and flexibility in their deployment onto the available software and hardware resources. Such flexibility greatly enhances modellers’ ability to re-configure the CIAS coupled models to answer different questions, thus tracking evolving policy needs. It also allows rigorous testing of the robustness of IA modelling results to the use of different component modules representing the same processes (for example, the economy). Such processes are often modelled in very different ways, using different paradigms, at the participating institutions. An illustrative application to the study of the relationship between the economy and the earth’s climate system is provided.

A management architecture for active networks

In this paper we present an architecture for network and applications management, which is based on the Active Networks paradigm and shows the advantages of network programmability. The stimulus to develop this architecture arises from an actual need to manage a cluster of active nodes, where it is often required to redeploy network assets and modify nodes connectivity. In our architecture, a remote front-end of the managing entity allows the operator to design new network topologies, to check the status of the nodes and to configure them. Moreover, the proposed framework allows to explore an active network, to monitor the active applications, to query each node and to install programmable traps. In order to take advantage of the Active Networks technology, we introduce active SNMP-like MIBs and agents, which are dynamic and programmable. The programmable management agents make tracing distributed applications a feasible task. We propose a general framework that can inter-operate with any active execution environment. In this framework, both the manager and the monitor front-ends communicate with an active node (the Active Network Access Point) through the XML language. A gateway service performs the translation of the queries from XML to an active packet language and injects the code in the network. We demonstrate the implementation of an active network gateway for PLAN (Packet Language for Active Networks) in a forty active nodes testbed. Finally, we discuss an application of the active management architecture to detect the causes of network failures by tracing network events in time.

A reconfigurable neural environment on active networks

This paper proposes the deployment of a neural network computing environment on Active Networks. Active Networks are packet-switched computer networks in which packets can contain code fragments that are executed on the intermediate nodes. This feature allows the injection of small pieces of codes to deal with computer network problems directly into the network core, and the adoption of new computing techniques to solve networking problems. The goal of our project is the adoption of a distributed neural network for approaching tasks which are specific of the computer network environment. Dynamically reconfigurable neural networks are spread on an experimental wide area backbone of active nodes (ABone) to show the feasibility of the proposed approach.

PRISM and ENES: a European approach to Earth system modelling

Europe's widely distributed climate modelling expertise, now organized in the European Network for Earth System Modelling (ENES), is both a strength and a challenge. Recognizing this, the European Union's Program for Integrated Earth System Modelling (PRISM) infrastructure project aims at designing a flexible and friendly user environment to assemble, run and post-process Earth System models. PRISM was started in December 2001 with a duration of three years. This paper presents the major stages of PRISM, including: (1) the definition and promotion of scientific and technical standards to increase component modularity; (2) the development of an end-to-end software environment (graphical user interface, coupling and I/O system, diagnostics, visualization) to launch, monitor and analyse complex Earth system models built around state-of-art community component models (atmosphere, ocean, atmospheric chemistry, ocean bio-chemistry, sea-ice, land-surface); and (3) testing and quality standards to ensure high-performance computing performance on a variety of platforms. PRISM is emerging as a core strategic software infrastructure for building the European research area in Earth system sciences. Copyright (c) 2005 John Wiley & Sons, Ltd.

A hierarchical distributed approach for mining molecular fragments

Recently, two approaches have been introduced that distribute the molecular fragment mining problem. The first approach applies a master/worker topology, the second approach, a completely distributed peer-to-peer system, solves the scalability problem due to the bottleneck at the master node. However, in many real world scenarios the participating computing nodes cannot communicate directly due to administrative policies such as security restrictions. Thus, potential computing power is not accessible to accelerate the mining run. To solve this shortcoming, this work introduces a hierarchical topology of computing resources, which distributes the management over several levels and adapts to the natural structure of those multi-domain architectures. The most important aspect is the load balancing scheme, which has been designed and optimized for the hierarchical structure. The approach allows dynamic aggregation of heterogenous computing resources and is applied to wide area network scenarios.

Artificial ants for active routing

Ant colonies in nature provide a good model for a distributed, robust and adaptive routing algorithm. This paper proposes the adoption of the same strategy for the routing of packets in an Active Network. Traditional store-and-forward routers are replaced by active intermediate systems, which are able to perform computations on transient packets, in a way that results very helpful for developing and dynamically deploying new protocols. The adoption of the Active Networks paradigm associated with a cooperative learning environment produces a robust, decentralized routing algorithm capable of adapting to network traffic conditions.

Influence-matrix diagnostic of a data assimilation system

The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society

Vision 2020 - A whole life-cycle information management system for built environments

A whole life-cycle information management vision is proposed, the organizational requirements for the realization of the scenario is investigated. Preliminary interviews with construction professionals are reported. Discontinuities at information transfer throughout life-cycle of built environments are resulting from lack of coordination and multiple data collection/storage practices. A more coherent history of these activities can improve the work practices of various teams by augmenting decision making processes and creating organizational learning opportunities. Therefore, there is a need for unifying these fragmented bits of data to create a meaningful, semantically rich and standardized information repository for built environment. The proposed vision utilizes embedded technologies and distributed building information models. Two diverse construction project types (large one-off design, small repetitive design) are investigated for the applicability of the vision. A functional prototype software/hardware system for demonstrating the practical use of this vision is developed and discussed. Plans for case-studies for validating the proposed model at a large PFI hospital and housing association projects are discussed.

Parallel and distributed computing with Java

The Java language first came to public attention in 1995. Within a year, it was being speculated that Java may be a good language for parallel and distributed computing. Its core features, including being objected oriented and platform independence, as well as having built-in network support and threads, has encouraged this view. Today, Java is being used in almost every type of computer-based system, ranging from sensor networks to high performance computing platforms, and from enterprise applications through to complex research-based.simulations. In this paper the key features that make Java a good language for parallel and distributed computing are first discussed. Two Java-based middleware systems, namely MPJ Express, an MPI-like Java messaging system, and Tycho, a wide-area asynchronous messaging framework with an integrated virtual registry are then discussed. The paper concludes by highlighting the advantages of using Java as middleware to support distributed applications.

Reach & grasp therapy: Design and control of a 9-DOF robotic neuro-rehabilitation system

This paper presents the Gentle/G integrated system for reach & grasp therapy retraining following brain injury. The design, control and integration of an experimental grasp assistance unit is described for use in robot assisted stroke rehabilitation. The grasp assist unit is intended to work with the hardware and software of the Gentle/S robot although the hardware could be adapted to other rehabilitation applications. When used with the Gentle/S robot a total of 6 active and 3 passive degrees of freedom are available to provide active, active assist or passive grasp retraining in combination with reaching movements in a reach-grasp-transfer-release sequence.