The computational Grid is an infrastructure which enables the execution of applications demanding huge computing resources. Hence, it can be the right environment for large-scale Multi-agent based simulation (MABS) applications. However, due to the nature of the Grid and the characteristics of MABS, achieving optimum performance poses a great challenge. Performance study of MABS applications is therefore a necessary undertaking which requires an understanding of these characteristics and the extent of their influence. Moreover, owing to the dynamicity and heterogeneity of the Grid, it is difficult to achieve performance gains without a middleware support for application deployment and dynamic reconfiguration. This paper presents a study of the key features of MABS applications that affect performance and proposes a supportive middleware to MABS platforms. Experiments show that the proposed middleware can bring performance improvement for MABS applications on the Grid.

Multi-agent based simulation (MABS) is a discrete event simulation technique used to study complex systems with entities having social and autonomous behavior. MABS applications are characterized by unpredictable execution behavior and high communication-to-computation ratio. In this paper, we propose an adaptation strategy to support efficient execution of large-scale MABS applications on typical Grid infrastructures. To achieve this objective, the behavior of MABS applications and the execution environment is investigated, in order to constantly obtain performance prediction models. These models will then be used to realize dynamic load balancing and resource allocation schemes. We discuss our basic approach, initial experimental results, the planned future research and an application of our research in the transportation and logistics simulation domain.

Agent platforms provide a framework for development and execution of parallel applications such as multi-agent based simulation (AMBS). However, these platforms have limitations to support large-scale MABS applications in practice. This paper aims at investigating and improving the performance of an agent platform with a AMBS workload in distributed environments. We carried out an experimental study with the JADE framework as our agent platform. The experiments show the performance characteristics of the workload and that JADE does not scale well due to message transport and agent directory service limitations. We propose solutions to overcome these performance bottlenecks and facilitate the efficient execution of AMBS in a distributed environment. Initial experimental results demonstrate the feasibility of the proposed approaches.

Distributed simulation has traditionally suffered from synchronization constraints that reduce the speedup significantly below the theoretical maximum. One solution approach are optimistic synchronization algorithms, allowing some nodes to advance in model time. In this paper, we present a novel algorithm that does not share the typical rollback costs of optimistic simulation, at the expense of restrictions on the design of simulation models. We have implemented that algorithm in an agent-based simulation framework, and evaluate its performance gains through measurements on actual simulation models.

A major requirement for Grid application developers is ensuring performance and scalability of their applications. Predicting the performance of an application demands understanding its specific features. This paper discusses performance modeling and prediction of multi-agent based simulation (MABS) applications on the Grid. An experiment conducted using a synthetic MABS workload explains the key features to be included in the performance model. The results obtained from the experiment show that the prediction model developed for the synthetic workload can be used as a guideline to understand to ,estimate the performance characteristics of real world simulation applications.

Using simulation environments to support mobile distributed application development has many benefits. Since mobile devices can be modeled as autonomous intelligent agents, the multi agent based simulation (MABS) approach is useful for such applications. In this paper, we propose a MABS platform on the computational Grid for mobile distributed computing. A prototype of the proposed platform is implemented and its performance characteristics are studied The findings of the experiment show that a Grid based MABS platform can provide a scalable simulation environment for mobile distributed applications.

This paper provides a survey and analysis of applications of Agent Based Simulation (ABS). A framework for describing and assessing the applications is presented and systematically applied. A general conclusion from the study is that even if ABS seems a promising approach to many problems involving simulation of complex systems of interacting entities, it seems as the full potential of the agent concept and previous research and development within ABS often is not utilized. We illustrate this by providing some concrete examples. Another conclusion is that important information of the applications, in particular concerning the implementation of the simulator, was missing in many papers. As an attempt to encourage improvements we provide some guidelines for writing ABS application papers.