Analytical Model to Evaluate the Performance of Mobile Agents in a Generic Network Topology

Arantes, Juliana Amaral; Westphall, Carlos Becker; Custódio, Ricardo Felipe; Chaves, Shirlei Aparecida de

doi:10.1007/s10922-010-9173-x

Cited by 1 publication

(1 citation statement)

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“…By using SNMP (simple network management protocol), Rantes et al developed a model for evaluating mobile agent performance factors. After conducting many experiments, the results mentioned that the mobile agent performance depends on the network management and some parameters related to a network topology, network latency [2]. Holt et al also used SNMP to analysis mobile agent performance factors.…”

Section: Related Workmentioning

confidence: 99%

Improve Mobile Agent Performance by using Knowledge-Based Content

Ahmed¹,

AL-Kharj²

2018

ijacsa

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Abstract-Mobile agent technology is one of the mobile computing areas. This technology could be used in several types of applications, such as cloud computing, e-commerce, databases, distributed systems management, network management, etc. The purpose of this paper is to propose a new model for increasing the mobile agent systems performance. The performance is considered as one of the important factors that makes the system reliable. This paper suggests a knowledge-based content to be used to improve the mobile agent systems performance. In the beginning, this work started by conducting intensive survey about related models and mechanisms to investigate the gaps in the performance. A comparative discussion has been conducted between some researches issued and the proposed model. The proposed model has been described in full details based on the components. A scenario-based approach has been used to implement the proposed model by using .Net framework and C# language. The model has been tested and evaluated based on different scenarios. As findings, the overall performance has been improved by 83% when the knowledge-based content is used. In addition, the system performance will improve automatically by the time because the content of the knowledge is increased. The proposed model is suitable to be used in any type of mobile agent applications. The originality of the model is based on conducted survey and own knowledge.

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Section: Related Workmentioning

confidence: 99%