Georgios K. Theodoropoulos

Large scale agent-based simulation on the grid

The development of many complex simulation applications requires collaborative effort from researchers with different domain knowledge and expertise, possibly at different locations. These simulation systems often require huge computing resources and data sets, which can be geographically distributed. In order to support collaborative model development and to cater for the increasing complexity of such systems, it is necessary to harness distributed resources over the Internet. The emergence of Grid technologies provides exciting new opportunities for large-scale distributed simulation, enabling collaboration and the use of distributed computing resources, while also facilitating access to geographically distributed data sets. This paper presents HLA_Grid_RePast, a middleware platform for executing large scale collaborating RePast agent-based models on the Grid. The paper also provides performance results from a deployment of the system between UK and Singapore.

Distributed simulation of agent-based systems with HLA

In this article we describe HLA_AGENT, a tool for the distributed simulation of agent-based systems, which integrates the SIM_AGENT agent toolkit and the High Level Architecture (HLA) simulator interoperability framework. HLA_AGENT offers enhanced simulation scalability and allows interoperation with other HLA-compliant simulators, promoting simulation reuse. Using a simple Tileworld example, we show how HLA_AGENT can be used to flexibly distribute a SIM_AGENT simulation so as to exploit available computing resources. We present experimental results that illustrate the performance of HLA_AGENT on a Linux cluster running a distributed version of Tileworld and compare this with the original nondistributed SIM_AGENT version.

e-Voting Requirements and Implementation

The level of research that e-voting has attracted is a testimony of its importance as a key element in the implementation of e-government. It is argued that the ease with which voting can be performed will increase participation and enhance accountability. This convenience however, generates a set of specific requirements, not least the ability of the underlying distributed system to model the behaviour of manual systems. More specifically, the elimination of direct physical intervention entails a careful management of the implications of virtual participation. The scope of this work concerns the identification and integration of specific mechanisms for addressing issues of security, privacy and accountability. The aim of this paper is to present a case study on the design and implementation of an e-voting prototype system, and to provide a context for the selection and deployment of relevant mechanisms.

An adaptive load management mechanism for distributed simulation of multi-agent systems

The paper presents a load management mechanism for distributed simulations of multi-agent systems. The mechanism minimizes the cost of accessing the shared state in the distributed simulation by dynamically redistributing shared state variables according to the access pattern of the simulation model. To evaluate the effectiveness and performance of the mechanism, a series of benchmark experiments were performed using the PDES-MAS framework for distributed simulation of multi-agent systems. Although preliminary, the results indicate that the proposed mechanism significantly reduces the overall access cost of the system.

Large Scale Distributed Simulation on the Grid

The developmentof many complex siumulation applications requires collaborrrtive effortfrom reseachers with different domain knowledge and expertise,possibly at different locations. These simulations systems often require huge computing resources and data set, which may be geo- graphically distribyted, In ordr to support collaborative model development and to cater for the increasing comoplex- ity of such systems, it is necessary to harness distributed resources over the Internet. the emergence of Grid tech nologies provide exciting new opportunities for large scale distributed simulation, enabling collaboration and the use of distributed computing resources, while also facilitating access to geographically distributed data sets. This paper discusses the research challenges that must be addresses before these opportunities can be exploited and presents HLA-GRID_REPast, a system for executing large scale distributed simulations of agent based systems over the Grid.

Intelligent management of data driven simulations to support model building in the social sciences

Artificial intelligence (AI) can contribute to the management of a data driven simulation system, in particular with regard to adaptive selection of data and refinement of the model on which the simulation is based. We consider two different classes of intelligent agent that can control a data driven simulation: (a) an autonomous agent using internal simulation to test and refine a model of its environment and (b) an assistant agent managing a data-driven simulation to help humans understand a complex system (assisted model-building). In the first case the agent is situated in its environment and can use its own sensors to explore the data sources. In the second case, the agent has much less independent access to data and may have limited capability to refine the model on which the simulation is based. This is particularly true if the data contains subjective statements about the human view of the world, such as in the social sciences. For complex systems involving human actors, we propose an architecture in which assistant agents cooperate with autonomous agents to build a more complete and reliable picture of the observed system.

Agents, games and HLA ☆

Over the past decade, there has been a growing interest in utilising intelligent agents in computer games and virtual environments. At the same time, computer game research and development has increasingly drawn on technologies and techniques originally developed in the large scale distributed simulation community, such as the HLA IEEE standard for simulator interoperability. In this paper, we address a central issue for HLA-based games, namely the development of HLA-compliant game agents. We present HLA_AGENT, an HLA-compliant version of the SIM_AGENT toolkit for building cognitively rich agents. We outline the changes necessary to the SIM_AGENT toolkit to allow integration with the HLA, and show that, given certain reasonable assumptions, all necessary code can be generated automatically from the FOM and the object class publications and subscriptions. The integration is transparent in the sense that the existing SIM_AGENT code runs unmodified and the agents are unaware that other parts of the system are running remotely. We present some preliminary performance results, which indicate that the overhead introduced by the HLA extension is modest even for lightweight agents with limited computational requirements. � 2005 Elsevier B.V. All rights reserved.

Robust and Skew-resistant Parallel Joins in Shared-Nothing Systems

The performance of joins in parallel database management systems is critical for data intensive operations such as querying. Since data skew is common in many applications, poorly engineered join operations result in load imbalance and performance bottlenecks. State-of-the-art methods designed to handle this problem offer significant improvements over naive implementations. However, performance could be further improved by removing the dependency on global skew knowledge and broadcasting. In this paper, we propose PRPQ (partial redistribution & partial query), an efficient and robust join algorithm for processing large-scale joins over distributed systems. We present the detailed implementation and a quantitative evaluation of our method. The experimental results demonstrate that the proposed PRPQ algorithm is indeed robust and scalable under a wide range of skew conditions. Specifically, compared to the state-of-art PRPD method, we achieve 16% - 167% performance improvement and 24% - 54% less network communication under different join workloads.

Interest management for distributed virtual environments: A survey

The past two decades have witnessed an explosion in the deployment of large-scale distributed simulations and distributed virtual environments in different domains, including military and academic simulation systems, social media, and commercial applications such as massively multiplayer online games. As these systems become larger, more data intensive, and more latency sensitive, the optimisation of the flow of data, a paradigm referred to as interest management, has become increasingly critical to address the scalability requirements and enable their successful deployment. Numerous interest management schemes have been proposed for different application scenarios. This article provides a comprehensive survey of the state of the art in the design of interest management algorithms and systems. The scope of the survey includes current and historical projects providing a taxonomy of the existing schemes and summarising their key features. Identifying the primary requirements of interest management, the article discusses the trade-offs involved in the design of existing approaches.

Medieval military logistics: a case for distributed agent-based simulation

Historical studies are frequently perceived to be characterised as clear narratives defined by a series of fixed events or actions. In reality, even where critical historic events may be identified, historic documentation frequently lacks corroborative detail that supports verifiable interpretation. Consequently, for many periods and areas of research, interpretation may rarely rise above the level of unproven assertion and is rarely tested against a range of evidence. Simulation provides an opportunity to break cycles of academic claim and counter-claim. This paper discusses the development and utilisation of large scale distributed Agent-based simulations designed to investigate the medieval military logistics in order to generate new evidence to supplement existing historical analysis. The work aims at modelling logistical arrangements relating to the battle of Manzikert (AD 1071), a key event in Byzantine history. The paper discusses the distributed simulation infrastructure and provides an overview of the agent models developed for this exercise.