A Framework for Developing Agent-Based Distributed Applications

Oey, Michel; Splunter, Sander van; Ogston, Elth; Warnier, Martijn; Brazier, Frances M. T.

doi:10.1109/wi-iat.2010.134

Cited by 7 publications

(6 citation statements)

References 13 publications

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“…AETOS is implemented and evaluated in Protopeer [Galuba et al, 2009], a prototyping toolkit for distributed systems. A concurrent implementation of AE-TOS in the AgentScape simulation framework [Oey et al, 2010] confirms the results of Protopeer. the selected experimental settings.…”

Section: Experimental Evaluationsupporting

confidence: 66%

“…Finally, note that the coordination performed in the top level assumes a synchronous communication for the matters of simplicity in the illustration of the algo-rithms. Nonetheless, a concurrent version of the top level in AETOS is implemented in the simulation framework of AgentScape [Oey et al, 2010]. In contrast to the top level, the gossiping realizations of the bottom and middle level tolerate the lack of concurrency with various solutions discussed by Jelasity et al [2007].…”

Section: Algorithmmentioning

confidence: 99%

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Adaptive Self-Organization in Distributed Tree Topologies

Pournaras

Warnier

Brazier

2014

International Journal of Distributed Systems and Technologies

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Tree topologies are often deployed in large-scale distributed systems to structure a hierarchical communication. Building and maintaining overlay networks self-organized in tree topologies is challenging to achieve in dynamic environments. Performance trade-offs between resilience to failures and message overhead need to be considered. This paper introduces eight adaptation strategies that provide a higher abstraction, modularity and reconfigurability in the tree self-organization process. Performance can be further enhanced by dynamically changing strategies during system runtime. Experimental evaluation illustrates the performance trade-offs and properties of adaptation strategies.

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Section: Experimental Evaluationsupporting

confidence: 66%

Section: Algorithmmentioning

confidence: 99%

Adaptive Self-Organization in Distributed Tree Topologies

Pournaras

Warnier

Brazier

2014

International Journal of Distributed Systems and Technologies

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“…JADE is identified as the one with the best messaging performance. A comparative analysis of JADE, AgentScape [31] and MadKit [17] is performed in [4], using different performance benchmarks. The results indicate that the messaging performance of JADE is superior to the one of the other MAPs.…”

Section: Multi-agent Systems and Platformsmentioning

confidence: 99%

Enabling scalable and fault-tolerant multi-agent systems by utilizing cloud-native computing

Dähling

Razik

Monti

2021

Auton Agent Multi-Agent Syst

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Multi-agent systems (MAS) represent a distributed computing paradigm well suited to tackle today’s challenges in the field of the Internet of Things (IoT). Both share many similarities such as the interconnection of distributed devices and their cooperation. The combination of MAS and IoT would allow the transfer of the experience gained in MAS research to the broader range of IoT applications. The key enabler for utilizing MAS in the IoT is the ability to build large-scale and fault-tolerant MASs since IoT concepts comprise possibly thousands or even millions of devices. However, well known multi-agent platforms (MAP), e. g., Java Agent DE-velopment Framework (JADE), are not able to deal with these challenges. To this aim, we present a cloud-native Multi-Agent Platform (cloneMAP) as a modern MAP based on cloud-computing techniques to enable scalability and fault-tolerance. A microservice architecture is used to implement it in a distributed way utilizing the open-source container orchestration system Kubernetes. Thereby, bottlenecks and single-points of failure are conceptually avoided. A comparison with JADE via relevant performance metrics indicates the massively improved scalability. Furthermore, the implementation of a large-scale use case verifies cloneMAP’s suitability for IoT applications. This leads to the conclusion that cloneMAP extends the range of possible MAS applications and enables the integration with IoT concepts.

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“…We have adopted the Agentscape middleware [16] for sys tem implementation because of its support for: (i) scalabil ity: we needed to be able to expand the system by adding as many nodes as required, without the need to change the overall architecture; this is straightforward in Agentscape because new hosts (physical nodes) can be combined with existing locations (logical nodes) at will, and (ii) mobile agents: so the system is ready for any possible change that…”

Section: Implementation and Deploymentmentioning

confidence: 99%

Market intelligence and price adaptation

Elakehal¹,

Padget

2012

Proceedings of the 14th Annual International Conference on Electronic Commerce

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In the context of e-commerce, it is critical for a retailing com pany to be able to assess the market and respond quickly to changes in competition and/or service levels and availability of its products. If the company operates globally, and the geographical constraints on the supplier are different from those on the consumer, it is even more crucial to assess each market with respect to its characteristics and dynamically price every individual product accordingly. In this paper we report on an agent-based distributed system that was devel oped to support the retailing operations of one of the largest online book sellers in the UK, which has millions of books on offer and operates internationally in a number of market places. The system supports the collection of market data, processing of this data, and applying dynamically one of set of predefined pricing patterns. We describe the principles on which the price adaptation is based, the (long-running and proven successful) distributed scalable software architecture that supports it, illustrate how the mechanism copes with some typical situations system that arise and highlight some of the lessons learned from the development experience.

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A Framework for Developing Agent-Based Distributed Applications

Cited by 7 publications

References 13 publications

Adaptive Self-Organization in Distributed Tree Topologies

Adaptive Self-Organization in Distributed Tree Topologies

Enabling scalable and fault-tolerant multi-agent systems by utilizing cloud-native computing

Market intelligence and price adaptation

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