A Genetic-Algorithm-Based Routing Optimization Scheme for Overlay Network

Lu, Jun; Cheng, Wengang

doi:10.1109/icnc.2007.37

Cited by 3 publications

(3 citation statements)

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“…A common approach for integrating various objectives in a genetic algorithm is to use a cost function that linearly combines several objectives as a weighted sum [6,21,25]. Although most of these approaches [22,32,34] achieved rapid convergence rates while producing overlay networks that satisfied the given constraints, to our knowledge, the methods were not applied at run time to address dynamic changes in the network's environment.…”

Section: Related Workmentioning

confidence: 96%

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Plato: a genetic algorithm approach to run-time reconfiguration in autonomic computing systems

et al. 2010

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Increasingly, applications need to be able to selfreconfigure in response to changing requirements and environmental conditions. Autonomic computing has been proposed as a means for automating software maintenance tasks. As the complexity of adaptive and autonomic systems grows, designing and managing the set of reconfiguration rules becomes increasingly challenging and may produce inconsistencies. This paper proposes an approach to leverage genetic algorithms in the decision-making process of an autonomic system. This approach enables a system to dynamically evolve target reconfigurations at run time that balance tradeoffs between functional and non-functional requirements in response to changing requirements and environmental conditions. A key feature of this approach is incorporating system and environmental monitoring information into the genetic algorithm such that specific changes in the environment automatically drive the evolutionary process towards new viable solutions. We have applied this geneticalgorithm based approach to the dynamic reconfiguration of a collection of remote data mirrors, demonstrating an effective decision-making method for diffusing data and minimizing operational costs while maximizing data reliability

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Section: Related Workmentioning

confidence: 96%

“…Genetic algorithms also have been used to design overlay multicast networks for data distribution [6,22,32,34]. These overlay networks must balance the competing goals of diffusing data across the network as efficiently as possible while minimizing expenses.…”

Section: Related Workmentioning

confidence: 99%

Plato: a genetic algorithm approach to run-time reconfiguration in autonomic computing systems

et al. 2010

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“…The paper presented in [4] studies an optimization scheme for determining the trade-off between two routing cost metrics i.e., delay and bandwidth. Another application on determination of trade-off between the coexisting networks is accounted in [5] which is analysed in terms of transmission capacity.…”

Section: Introductionmentioning

confidence: 99%

A Trade-off Analysis of Quality of Service (QoS) Metrics Towards Routing in Mobile Networks: MOGA Based Approach

Rudra

Thakurta

Poddar

2015

Advances in Intelligent Systems and Computing

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The trade-off analysis between two QoS metrics towards efficient routing in mobile networks is proposed in this paper. For such analysis the behavioural natures of end-to-end transmission cost and hop-count as QoS metrics are accounted in discrete domain and subsequently, the probability density functions (pdf) of those important factors are determined. The pdf of these are transformed into continuous domain to perform mathematical operation and subsequent analysis is presented to obtain the optimal routing path(s). In this context, a multi objective optimization (MOO) on these parameters is proposed and more refined results among all possible solutions are obtained accordingly. The diverse set of possible solutions for such analysis is explored through a Multi Objective Genetic Algorithm (MOGA) based approach.

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