Swarm intelligence based classifiers

Zahiri, Seyed Hamid; Seyedin, Seyed Alireza

doi:10.1016/j.jfranklin.2005.12.006

Cited by 53 publications

(17 citation statements)

References 17 publications

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“…In this work we will propose a PSO-based procedure to dynamically adjustment of RED parameters, namely, max th and min th . PSO, which is tailored for optimizing difficult numerical functions and is based on metaphor of human social interaction, is capable of mimicking the ability of human societies to process knowledge [6]. It has roots in two main component methodologies: artificial life (such as bird flocking, fish schooling and swarming); and evolutionary computation.…”

Section: Preliminaries: Red and Pso Algorithmsmentioning

confidence: 99%

“…Subject to : Bottleneck U tilization > T arget U tilization (6) Note that the T arget U tilization is the lowest acceptable level of utilization that is determined by the designer in range of (0, 1]. Although low values lead to smaller average queue length, its side effect is waste of the network resources.…”

Section: Minimize Avg(t)mentioning

confidence: 99%

“…In this paper we aim at finding a dynamic approach for tuning of RED parameters to meet all requirements of an efficient AQM scheme, independently of the load range. For this purpose, this paper uses the PSO algorithm [6] for tuning RED parameters.…”

Section: Introductionmentioning

confidence: 99%

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An improvement over RED algorithm by using particle swarm optimization

Jamali

Zahedi

2010

IEICE Electron. Express

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Abstract:One of the most challenging issues in Random Early Detection (RED) algorithm is how to set its parameters to achieve high performance for the dynamic conditions of the network. While original RED uses fixed values for its parameters, this paper proposes a novel algorithm, in which particle swarm optimization (PSO) technique is used to dynamic tuning of RED's parameters. For this purpose, we formulate the active queue management issue as an optimization problem to be solved by PSO algorithm. Then, we employ PSO technique to direct the system to its optimum point. Simulation results show that the proposed algorithm behaves remarkably better than RED in terms of queue size, number of dropped packets, bottleneck utilization and global stability. Keywords: congestion control, RED, particle swarm optimization (PSO) Classification: Science and engineering for electronics

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Section: Preliminaries: Red and Pso Algorithmsmentioning

confidence: 99%

Section: Minimize Avg(t)mentioning

confidence: 99%

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An improvement over RED algorithm by using particle swarm optimization

Jamali

Zahedi

2010

IEICE Electron. Express

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“…The initial swarm of particles is randomly generated. Then k-means algorithm is performed and repeated at regular intervals [11]. Particles in different sub swarm (cluster) at early stage of the simulation can end up in the same local optimum, it means that those clusters are similar and merge by creating a new sub swarm.…”

Section: Fig1 Main Algorithm Pseudo Codementioning

confidence: 99%

A new approach on particle swarm optimization for multimodal functions

Afsahi

Meybodi

2009

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems

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This paper describes a technique that extends PSO to locate multiple optima on a multimodal functions. In this paper, we present a new algorithm based on clustering particles to identify niches. For that we employ the standard k-means clustering algorithm which can identify the number of clusters adaptively. In each niche we used artificial immune system algorithm to determine the true members of it. Experimental results show that the proposed algorithm can successfully locate all optimum solutions on a small set of test functions during all simulation runs.

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“…This algorithm formulates the active queue management issue as an optimization problem and employs PSO technique [7]- [11] to Manuscript received November 11, 2012; revised March 5, 2013. Shahram Jamali is with the Electrical and Computer Engineering Department University of Mohaghegh Ardabili, Ardabil, Iran (e-mail: Jamali@iust.ac.ir).…”

Section: Introductionmentioning

confidence: 99%

An Active Queue Management for High Bandwidth-Delay Product Networks

Jamali¹,

Zahedi²

2013

IJCTE

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Abstract-As the per-flow product of bandwidth and latency increases, TCP/RED becomes inefficient and prone to instability. To address this problem we are going to design a novel active queue management (AQM) that supports TCP to achieve high performance in such networks. This paper proposes a novel algorithm, in which, particle swarm optimization (PSO) technique is used to dynamic tuning of RED's parameters. This algorithm formulates the active queue management issue as an optimization problem and employs PSO technique to direct it to its optimum point. Dynamic tuning of parameters helps the proposed algorithm to be adapted to special situations such as high bandwidth and large delays. Simulation results show that the proposed algorithm behaves remarkably better than RED in terms of queue size, number of dropped packets, and bottleneck utilization for these networks.Index Terms-AQM, RED, high bandwidth delay product.

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Swarm intelligence based classifiers

Cited by 53 publications

References 17 publications

An improvement over RED algorithm by using particle swarm optimization

An improvement over RED algorithm by using particle swarm optimization

A new approach on particle swarm optimization for multimodal functions

An Active Queue Management for High Bandwidth-Delay Product Networks

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