An Aggregation Technique for Large-Scale PEPA Models with Non-Uniform Populations

Performance analysis based on modelling consists of two major steps: model construction and model analysis. Formal modelling techniques significantly aid model construction but can exacerbate model analysis. In particular, here we consider the analysis of large-scale systems which consist of one or more entities replicated many times to form large populations. The replication of entities in such models can cause their state spaces to grow exponentially to the extent that their exact stochastic analysis becomes computationally expensive or even infeasible. In this paper, we propose a new approximate aggregation algorithm for a class of large-scale PEPA models. For a given model, the method quickly checks if it satisfies a syntactic condition, indicating that the model may be solved approximately with high accuracy. If so, an aggregated CTMC is generated directly from the model description. This CTMC can be used for efficient derivation of an approximate marginal probability distribution over some of the model's populations. In the context of a large-scale client-server system, we demonstrate the usefulness of our method

The development of a novel large area building integrated solar collector for pool heating

Unglazed solar collectors have often been used a means of providing low cost heating to swimming pools. However, these systems are typically polymer style “mats” that are laid on top of a roof, often leading to poor aesthetics due to their lack of integration with the building itself. This study charts the development of a novel large area unglazed building integrated solar pool heating system (BIT), based on long run sheet metal roofing, from its initial conceptualisation through to its implementation. It discusses the design of the building integrated solar collector modules, the assessment of their performance through theoretical modelling and experimental validation. Subsequently, it shows the scaling of laboratory scale testing to a large area array through modelling and discusses the performance of the system in the “as-built” configuration. In doing this, it provides a succinct illustration of the design process for the development of the University of Waikato’s building integrated pool heating system

Small-scale (≤6 kWe) stand-alone and grid-connected photovoltaic, wind, hydroelectric, biodiesel, and wood gasification system's simulated technical, economic, and mitigation analyses for rural regions in Western Australia

This research develops models and simulations of technical performance, net emission reductions, and discounted market values of thirteen small-scale (≤6 kWe) renewable energy projects. The research uses a simple methodology suitable for small private entities and governments to compare alternative investment options for both climate change mitigation and adaptation in the southwest of Western Australia. The system simulation and modelling results indicate that privately-owned, small-scale, grid-connected renewable energy systems were not competitive options for private entities relative to sourcing electricity from electricity networks, despite subsidies. The total discounted capital and operating costs, combined with the minimal mitigation potentials of the small-scale renewable energy systems resulted in unnecessarily high electricity costs and equivalent carbon prices, relative to grid-connection and large-scale clean energy systems. In contrast, this research suggests that small-scale renewable energy systems are cost-effective for both private entities and governments and exhibit good mitigation potentials when installed in remote locations far from the electricity network, mostly displacing diesel capacity

Applying Mean-field Approximation to Continuous Time Markov Chains

The mean-field analysis technique is used to perform analysis of a systems with a large number of components to determine the emergent deterministic behaviour and how this behaviour modifies when its parameters are perturbed. The computer science performance modelling and analysis community has found the mean-field method useful for modelling large-scale computer and communication networks. Applying mean-field analysis from the computer science perspective requires the following major steps: (1) describing how the agents populations evolve by means of a system of differential equations, (2) finding the emergent deterministic behaviour of the system by solving such differential equations, and (3) analysing properties of this behaviour either by relying on simulation or by using logics. Depending on the system under analysis, performing these steps may become challenging. Often, modifications of the general idea are needed. In this tutorial we consider illustrating examples to discuss how the mean-field method is used in different application areas. Starting from the application of the classical technique, moving to cases where additional steps have to be used, such as systems with local communication. Finally we illustrate the application of the simulation and uid model checking analysis techniques

An improved multi-agent simulation methodology for modelling and evaluating wireless communication systems resource allocation algorithms

Multi-Agent Systems (MAS) constitute a well known approach in modelling dynamical real world systems. Recently, this technology has been applied to Wireless Communication Systems (WCS), where efficient resource allocation is a primary goal, for modelling the physical entities involved, like Base Stations (BS), service providers and network operators. This paper presents a novel approach in applying MAS methodology to WCS resource allocation by modelling more abstract entities involved in WCS operation, and especially the concurrent network procedures (services). Due to the concurrent nature of a WCS, MAS technology presents a suitable modelling solution. Services such as new call admission, handoff, user movement and call termination are independent to one another and may occur at the same time for many different users in the network. Thus, the required network procedures for supporting the above services act autonomously, interact with the network environment (gather information such as interference conditions), take decisions (e.g. call establishment), etc, and can be modelled as agents. Based on this novel simulation approach, the agent cooperation in terms of negotiation and agreement becomes a critical issue. To this end, two negotiation strategies are presented and evaluated in this research effort and among them the distributed negotiation and communication scheme between network agents is presented to be highly efficient in terms of network performance. The multi-agent concept adapted to the concurrent nature of large scale WCS is, also, discussed in this paper

Towards Modelling and Analysing Non-Functional Properties of Systems of Systems

International audienceSystems of systems (SoS) are large-scale systems composed of complex systems with difficult to predict emergent properties. One of the most significant challenges in the engineering of such systems if how to predict their Non-Functional Properties (NFP) such as performance and security, and more specifically, how to model NFP when the overall system functionality is not available. In this paper, we identify, describe and analyse challenges to modelling and analysing the performance and security NFP of SoS. We define an architectural framework to SoS NFP prediction based on the modelling of system interactions and their impacts. We adopt an Event Driven Architecture to support this modelling, as it allows for more realistic and flexible NFP simulation, which enables more accurate NFP prediction. A framework integrating the analysis of several NFP allows for exploring the impacts of changes made to accommodate issues on one NFP on other NFPs

Parallel pair-wise interaction for multi-agent immune systems modelling

Agent Based Modelling (ABM), is an approach for modelling dynamic systems and studying complex and emergent behaviour. ABM approach is a very common technique in biological domain due to high demand for a large scale analysis tool to collect and interpret information to solve biological problems. However, simulating large scale cellular level models (i.e. large number of agents/entities) require a high degree of computational power which is achievable through parallel computing methods such as Graphics Processing Units (GPUs). The use of parallel approaches in ABMs is growing rapidly specifically when modelling in continuous space system (particle based). Parallel implementation of particle based simulation within continuum space where agents contain quantities of chemicals/substances is very challenging. Pair-wise interactions are different abstraction to continuous space (particle) models which is commonly used for immune system modelling. This paper describes an approach to parallelising the key component of biological and immune system models (pair-wise interactions) within an ABM model. Our performance results demonstrate the applicability of this method to a broader class of biological systems with the same type of cell interactions and that it can be used as the basis for developing complete immune system models on parallel hardware

On the accuracy of modelling the dynamics of large space structures

Proposed space missions will require large scale, light weight, space based structural systems. Large space structure technology (LSST) systems will have to accommodate (among others): ocean data systems; electronic mail systems; large multibeam antenna systems; and, space based solar power systems. The structures are to be delivered into orbit by the space shuttle. Because of their inherent size, modelling techniques and scaling algorithms must be developed so that system performance can be predicted accurately prior to launch and assembly. When the size and weight-to-area ratio of proposed LSST systems dictate that the entire system be considered flexible, there are two basic modeling methods which can be used. The first is a continuum approach, a mathematical formulation for predicting the motion of a general orbiting flexible body, in which elastic deformations are considered small compared with characteristic body dimensions. This approach is based on an a priori knowledge of the frequencies and shape functions of all modes included within the system model. Alternatively, finite element techniques can be used to model the entire structure as a system of lumped masses connected by a series of (restoring) springs and possibly dampers. In addition, a computational algorithm was developed to evaluate the coefficients of the various coupling terms in the equations of motion as applied to the finite element model of the Hoop/Column