Active queue management algorithm based on particle swarm optimization

Wang, Junxiang; Bo-gang, Lin

doi:10.3724/sp.j.1087.2013.00390

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The highest congestion sign is introduced to inform the source when the queue becomes full; all the remaining packets that arrive are subsequently dropped. RED was initiated to overcome the pitfalls of TD technique, [9][10][11][12][13][14]. RED is one of the Active Queue Management (AQM) plans approach [15].…”

Section: Existing Algorithmsmentioning

confidence: 99%

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Waheed¹,

Khan²,

Zareei³

et al. 2020

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

Congestion control is one of the main obstacles in cyberspace traffic. Overcrowding in internet traffic may cause several problems; such as high packet hold-up, high packet dropping, and low packet output. In the course of data transmission for various applications in the Internet of things, such problems are usually generated relative to the input. To tackle such problems, this paper presents an analytical model using an optimized Random Early Detection (RED) algorithm-based approach for internet traffic management. The validity of the proposed model is checked through extensive simulation-based experiments. An analysis is observed for different functions on internet traffic. Four performance metrics are taken into consideration, namely, the possibility of packet loss, throughput, mean queue length and mean queue delay. Three sets of experiments are observed with varying simulation results. The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.

show abstract

Section: Existing Algorithmsmentioning

confidence: 99%

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Waheed¹,

Khan²,

Zareei³

et al. 2020

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Every particle constantly updates itself through pbest and gbest, and then a new population is created. At last, the whole population can comprehensively search the solution region [8].…”

Section: Particle Swarm Optimization Algorithmmentioning

confidence: 99%

Sustainability Assessment of Regional Water Resources Use Based on PSO-PPE

Jiang

Wang

2012

Computer and Computing Technologies in Agriculture V

View full text Add to dashboard Cite

Abstract. Aiming at poor valuing objectivity for indicator weight in sustainability assessment of water resources use (SAWRU), an indicator system and a projection pursuit evaluation model optimized by particle swarm optimization algorithm were structured for SAWRU, and then the method was applied to the SAWRU of Sanjiang Plain. The applied results indicated that the method not only avoided artificial disturbance when valuing indicator weight but also had the advantages of objective and precise assessment result, feasibility and availability. The assessment results showed that the sustainable grade of water resources use of Jiamusi, Shuangyashan and Jixi which located at Sanjiang Plain belonged to III, and the grade of the other regions of Sanjiang Plain belonged to IV. Thus, scientific water resource use scheme and reasonable socioeconomic development strategy need to be made based on the regional characteristics of water resources and socioeconomic development.

show abstract

Active queue management algorithm based on particle swarm optimization

Cited by 2 publications

References 0 publications

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Sustainability Assessment of Regional Water Resources Use Based on PSO-PPE

Contact Info

Product

Resources

About