Performance evaluation for DRED discrete-time queueing network analytical model

Abdel-Jaber, Hussein; Woodward, M.E.; Thabtah, Fadi; Abu-Ali, Amer

doi:10.1016/j.jnca.2007.09.003

Cited by 20 publications

(20 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results of the analysis and modeling are, (1) the balance equations, (2) the equilibrium probabilities and (3) the performance measures numbers, e.g., MQL, throughput, average queueing delay, etc. Discretetime queueing are also used to analyze queueing systems that employ AQM as of congestion control methods, such as DRED models, 11,12,14,15 and GRED models. 14 Hereunder we summarizes relevant research works and then examines two common approaches: RED and TLRAR since we compare with them in the experimental section.…”

Section: Related Workmentioning

confidence: 99%

“…The new model in Ref. 15 was built by modeling two queue nodes where queue node 1 has a higher priority than the queue node 2 in receiving packets generated from outside the network. In Ref.…”

Section: Related Workmentioning

confidence: 99%

“…Another way of controlling congestion is to analyze and model queueing network systems based on AQM techniques [11][12][13][14][15][16] such as using discrete-time queues. 17 A discrete-time queue uses a time unit called a slot.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modeling discrete-time analytical models based on random early detection: Exponential and linear

Abdel-Jaber

Thabtah

Woodward

2015

Int. J. Model. Simul. Sci. Comput.

Self Cite

View full text Add to dashboard Cite

Congestion control is among primary topics in computer network in which random early detection (RED) method is one of its common techniques. Nevertheless, RED suffers from drawbacks in particular when its "average queue length" is set below the buffer's "minimum threshold" position which makes the router buffer quickly overflow. To deal with this issue, this paper proposes two discrete-time queue analytical models that aim to utilize an instant queue length parameter as a congestion measure. This assigns mean queue length (mql) and average queueing delay smaller values than those for RED and eventually reduces buffers overflow. A comparison between RED and the proposed analytical models was conducted to identify the model that offers better performance. The proposed models outperform the classic RED in regards to mql and average queueing delay measures when congestion exists. This work also compares one of the proposed models (RED-Linear) with another analytical model named threshold-based linear reduction of arrival rate (TLRAR). The results of the mql, average queueing delay and the probability of packet loss for TLRAR are deteriorated when heavy congestion occurs, whereas, the results of our RED-Linear were not impacted and this shows superiority of our model.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Modeling discrete-time analytical models based on random early detection: Exponential and linear

Abdel-Jaber

Thabtah

Woodward

2015

Int. J. Model. Simul. Sci. Comput.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Hussein Abdel-Jabed et. al [8] proposed a new analytical model based on DRED algorithm on two queue nodes queuing network. Lan Wang et.…”

Section: Related Workmentioning

confidence: 99%

A pre-emptive multiple queue based congestion control for different traffic classes in WSN

Sunitha¹,

Kumar

Brajesh

2014

International Conference on Circuits, Communication, Control and Computing

View full text Add to dashboard Cite

Abstract-Traffic in wireless sensor networks (WSN) exhibits a many-to-one pattern in which multiple source nodes send sensing data to a single sink node. Since bandwidth, processor and memory are highly constrained in WSN, packet loss is common when a great deal of traffic rushes to sink. The system must provide differentiated service to individual traffic classes. In this paper, a pre-emptive multiple queue based congestion control mechanism is proposed. To detect congestion and to provide QoS for high priority traffic multiple buffers are used. Using this mechanism, high system utilization, reduced packet waiting time, and reduced packet drop probability are achieved. An analytical model is developed to predict the performance of the proposed mechanism by calculating the performance measures including system throughput, drop probability of packets, and mean queue length. By comparing analytical and simulation results the effectiveness and accuracy of the model is demonstrated. Markovian process is used to develop the analytical model and ns-2 for evaluating the performance of the mechanism.

show abstract

“…In the meantime, much research has focused on performance improvement of interactive TCP congestion control schemes with an active queue management (AQM) mechanism. In [1], Abdel-Jaber et al proposed a new discrete-time queuing network analytical model based on the dynamic random early drop (DRED) algorithm to control congestion in the early stages of a two-queue node queuing network. In [6], Chen et al proposed a static state feedback controller and an observer-based controller for a class of TCP communication networks to achieve the desired queue size and guarantee asymptotic stability of the operating point.…”

Section: Introductionmentioning

confidence: 99%

Per-stream loss behavior of ∑MAP/M/1/K queuing system with a random early detection mechanism

Wang

Tseng

Chu

et al. 2009

Information Sciences

View full text Add to dashboard Cite

Performance evaluation for DRED discrete-time queueing network analytical model

Cited by 20 publications

References 11 publications

Modeling discrete-time analytical models based on random early detection: Exponential and linear

Modeling discrete-time analytical models based on random early detection: Exponential and linear

A pre-emptive multiple queue based congestion control for different traffic classes in WSN

Per-stream loss behavior of ∑MAP/M/1/K queuing system with a random early detection mechanism

Contact Info

Product

Resources

About