The development of ubiquitous and pervasive computing systems requires new approaches and paradigms. Mobile agent based approaches have received a great attention for developing distributed applications. Agents are programs that can migrate from a machine to another in a network and perform tasks on distant machines. However, it is difficult to estimate a priori the appropriate number of agents allowed to be spawned in the network without any global information or controller. Indeed, increasing agent population size, with cloning operation, will increase resource demands in the network, which would indirectly affect the network performance. This paper focuses on the problem of dynamic regulation of mobile agent population size in a distributed system and proposes an approach that takes inspiration from the immune system concepts. Simulations have been conducted and results are reported to show the effectiveness of the proposed approach.
Paper
Full text
An Adaptive Regulation Approach of Mobile Agent Population Size in Distributed Systems
Semantic Scholar · Computer Science · 2016
Abstract
The development of ubiquitous and pervasive computing systems requires new approaches and paradigms. Mobile agent based approaches have received a great attention for developing distributed applications. Agents are programs that can migrate from a machine to another in a network and perform tasks on distant machines. However, it is difficult to estimate a priori the appropriate number of agents allowed to be spawned in the network without any global information or controller. Indeed, increasing agent population size, with cloning operation, will increase resource demands in the network, which would indirectly affect the network performance. This paper focuses on the problem of dynamic regulation of mobile agent population size in a distributed system and proposes an approach that takes inspiration from the immune system concepts. Simulations have been conducted and results are reported to show the effectiveness of the proposed approach.