Mobile agent standards and available platforms

Perdikeas, Menelaos K.; Chatzipapadopoulos, Fotis G.; Venieris, Iakovos S.; Marino, Gennaro G.

doi:10.1016/s1389-1286(99)00076-6

Cited by 55 publications

(17 citation statements)

References 18 publications

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“…Using agents in telecommunication network area is not new; many mobile agents platforms are used in many projects (for more details see [11]), but our approach is however innovative for three reasons: (1) the use of behaviour to model network entities, (2) the use of behaviour to simulate the dynamicity of the network, and (3) the use of simple concept inspired from the human model to name these entities. In this light, many behaviours have been defined, but only four of them have been implemented and tested in order to find the best combination regarding the number of lost packets (Best Effort, Olympic or Premium).…”

Section: Discussionmentioning

confidence: 99%

Active Network Modelling and Simulation: A Behavioural Approach

Gaïti¹,

Merghem²

2002

Smart Networks

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Network environments become more and more complex in terms of new services, quality of service to handle and user demand for increasing throughput. All these facts have to be performed in real time (or alm ost), and consequently, network management and control are difficult to realise in this continuously changing environment. The network is now unpredictable and there is areal lack in the modelisation and simulation tools to handle this dynamicity. In this context, agents and multi-agent systems seem to be good candidates to provide a way to model and to manage the network dynamicity. This is due to the fact that agents can perform tasks in an autonomous, distributed, adaptable and cooperative manner. Our goal here is to model an active network by using a multi-agent approach and more precisely a behaviour based agent approach. Instead ofrepresenting the actions ofthe network elements by complex algorithms, we rather describe them by their behaviours which are usually simple and familiar words, inspired in part from human behaviour. On this basis, we have made simulations of an active network environment, and implemented different combinations of four individual behaviours by using a multi-agent platform called Swarm. Results ofthese simulations are significant and show that we do not loose important packets (with priority) any more when we introduce a behaviour in the nodes.

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Section: Discussionmentioning

confidence: 99%

Active Network Modelling and Simulation: A Behavioural Approach

Gaïti¹,

Merghem²

2002

Smart Networks

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“…From references [1][2][3] which have been published on mobile agents, we can easily define the concepts of mobile agent and mobile agent platform.…”

Section: Mobile Agents and Platformsmentioning

confidence: 99%

Mobile Agents in E-Learning Resource Management

Cheng

Wang

et al. 2006

Proceedings. Frontiers in Education. 36th Annual Conference

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This paper is devoted to mobile agents and their use for E-learning resource management. We provide a brief overview and an elaborate case study. The overview introduces the concept of mobile agent, enumerates the claimed benefits, and discusses the state of the art of application in this domain. In the case study, we use mobile agents with Learning Object Metadata and Right Expression Language description information to achieve a whole resource management process. The process shows how the prototype we have made works. We also contrast the performance to the client/server paradigm, which we have built for comparison purposes. At last, we conclude with a summary, lessons learned, and items for future work.

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“…The framework resides above a mobile agent platform (MAP) [4] and consists of a scheme for adaptive placement of multiple agents. These agents are responsible to deliver a native program to a remote processor according to a scheduling policy, provide the right input to this program, execute the code and process the results.…”

Section: Introductionmentioning

confidence: 99%

An agent‐based framework for parametric studies of numerical modelling problems in computational electromagnetics

Biniaris

Kostaridis

Kaklamani

et al. 2003

Int J Numerical Modelling

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SUMMARYIn this paper, we present the design of a generic agent-based framework for distributed parametric analysis of numerical modelling problems on a network of workstations and its application in computational electromagnetics (CEM). The entire infrastructure is based on a Master-Worker paradigm that utilizes mobile agents in order to gather information about the hosts of the network, transfer the native code there, handle its execution and collect the results. Such a framework enables scientists and engineers to perform simulations and parametric studies, in order to determine configurations and characteristics of the scenarios being modelled and, thereby, to greatly improve and shorten design processes. A case study in antenna modelling is presented, in order to test the efficiency of the developed framework.

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Mobile agent standards and available platforms

Cited by 55 publications

References 18 publications

Active Network Modelling and Simulation: A Behavioural Approach

Active Network Modelling and Simulation: A Behavioural Approach

Mobile Agents in E-Learning Resource Management

An agent‐based framework for parametric studies of numerical modelling problems in computational electromagnetics

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