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Middleware support for performance improvement of MABS applications in the Grid environment
Department of Systems and Software Engineering, School of Engineering, Blekinge Institute of Technology.
Department of Systems and Software Engineering, School of Engineering, Blekinge Institute of Technology.
Department of Systems and Software Engineering, School of Engineering, Blekinge Institute of Technology.
2008 (English)In: Multi-agent-based simulation VIII: International workshop, MABS 2007, Honolulu, HI, USA, May 15, 2007, revised and invited papers / [ed] Luis Antunes, Mario Paolucci & Emma Norling, Berlin: Springer Berlin/Heidelberg, 2008, 20-35 p.Conference paper, (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Berlin: Springer Berlin/Heidelberg, 2008. 20-35 p.
Series
Lecture notes in computer science, 0302-9743
National Category
Computer Science
Identifiers
URN: urn:nbn:se:hkr:diva-11439ISI: 000258329600003Libris ID: 11431164ISBN: 978-3-540-70915-2 (print)ISBN: 978-3-540-70916-9 (print)OAI: oai:DiVA.org:hkr-11439DiVA: diva2:679052
Conference
8th International Workshop on Multi-Agent-Based Simulation
Available from: 2013-12-13 Created: 2013-12-13 Last updated: 2013-12-17Bibliographically approved
In thesis
1. Multi-agent based simulations in the grid environment
Open this publication in new window or tab >>Multi-agent based simulations in the grid environment
2007 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The computational Grid has become an important infrastructure as an execution environment for scientific applications that require large amount of computing resources.  Applications which would otherwise be unmanageable or take a prohibitively longer execution time under previous computing paradigms can now be executed efficiently on the Grid within a reasonable time.

Multi-agent based simulation (MABS) is a methodology used to study and understand the dynamics of real world phenomena in domains involving interaction and/or cooperative problem solving where the participants are characterized by entities having autonomous and social behaviour.  For certain domains the size of the simulation is extremely large, intractable without employing adequate computing resources such as the Grid. 

Although the Grid has come with immense opportunities to resource demanding applications such as MABS, it has also brought with it a number of challenges related to performance.  Performance problems may have their origins either on the side of the computing infrastructure or the application itself, or both. 

This thesis aims at improving the performance of MABS applications by overcoming problems inherent to the behaviour of MABS applications.  It also studies the extent to which the MABS technologies have been exploited in the field of simulation and find ways to adapt existing technologies for the Grid.  It investigates performance monitoring and prediction systems in the Grid environment and their implementation for MABS application with the purpose of identifying application related performance problems and their solutions.

Our research shows that large-scale MABS applications have not been implemented despite the fact that many problem domains that cannot be studied properly with only partial simulation.  We assume that this is due to the lack of appropriate tools such as MABS platforms for the Grid.  Another important finding of this work is the improvement of application performance through the use of MABS specific middleware.

Place, publisher, year, edition, pages
Karlskrona: Department of Systems and Software Engineering, Blekinge Institute of Technology, 2007. 104 p.
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 2007:06
Keyword
Agenter (datorprogram)
National Category
Computer Science
Identifiers
urn:nbn:se:hkr:diva-11456 (URN)9789172951181 (ISBN)
Available from: 2013-12-16 Created: 2013-12-16 Last updated: 2013-12-16Bibliographically approved
2. Improving the performance of distributed multi-agent based simulation
Open this publication in new window or tab >>Improving the performance of distributed multi-agent based simulation
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This research investigates approaches to improve the performance of multi-agent based simulation (MABS) applications executed in distributed computing environments.  MABS is a type of micro-level simulation used to study dynamic systems consisting of interacting entities, and in some cases, the number of the simulated entities can be very large.  Most of the existing publicly available MABS tools are single-threaded desktop applications that are not suited for distributed execution.  For this reason, general-purpose multi-agent platforms with multi-threading support are sometimes used for deploying MABS on distributed resources.  However, these platforms do not scale well for large simulations due to huge communication overheads.  In this research, different strategies to deploy large scale MABS in distributed environments are explored, e.g., tuning existing multi-agent platforms, porting single-threaded MABS tools to distributed environment, and implementing a service oriented architecture (SOA) deployment model.

Although the factors affecting the performance of distributed applications are well known, the relative significance of the factors is dependent on the architecture of the application and the behaviour of the execution environment. We developed mathematical performance models to understand the influence of these factors and, to analyze the execution characteristics of MABS.  These performance models are then used to formulate algorithms for resource management and application tuning decisions.

The most important performance improvement solutions achieved in this thesis include: predictive estimation of optimal resource requirements, heuristics for generation of agent reallocation to reduce communication overhead and, an optimistic synchronization algorithm to minimize time management overhead.  Additional application tuning techniques such as agent directory caching and message aggregations for fine-grained simulations are also proposed.  These solutions were experimentally validated in different types of distributed computing environments.

Another contribution of this research is that all improvement measures proposed in this work are implemented on the application level.  It is often the case that the improvement measures should not affect the configuration of the computing and communication resources on which the application runs.  Such application level optimizations are useful for application developers and users who have limited access to remote resources and lack authorization to carry out resource level optimizations.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Institute of Technology, 2011. 213 p.
Series
Blekinge Institute of Technology doctoral dissertation series, ISSN 1653-2090 ; 2011:04
Keyword
agent based simulation, MABS, distributed systems, application performance
National Category
Computer Science
Identifiers
urn:nbn:se:hkr:diva-11457 (URN)9789172951983 (ISBN)
Available from: 2013-12-17 Created: 2013-12-16 Last updated: 2013-12-17Bibliographically approved

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