Simulations framework for network congestion avoidance algorithms using the OMNeT&amp;#x002B;&amp;#x002B; IDE

Buzura, Sorin; Dadarlat, Vasile; Peculea, Adrian; Iancu, Bogdan; Cebuc, Emil

doi:10.1109/roedunet.2013.6511758

Cited by 3 publications

(5 citation statements)

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“…Our experiments are performed by using the OMNet++ simulator with IDE toolkit, which is an object-oriented C++ component-based discrete event simulation framework primarily used for network simulation [19]. In our simulations we set the minimum queue length threshold for the proposed RED algorithm as = 10 and the maximum queue length threshold as = 30, both in the unites of packets.…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

“…Lower implementation complexity allows the proposed RED algorithm to satisfy the resource limited networking scenarios in WSNs, thus enabling the algorithm to meet the requirement of realtime sensor Cloud applications better than regular RED algorithms do. In addition, as shown in [19] using instantaneous queue length can improve RED performance for handling some special cases. For instance, when the queue is full but the average queue length is below the minimum threshold or between the two thresholds, it prevents RED from dropping a sufficient number of packets to avoid occurrence of network congestion.…”

Section: Model For Red Controlled Data Transmission In Sensormentioning

confidence: 98%

“…drop the arriving packet with probability ; (10) if the current packet is dropped then (11) = 0; (12) + +; (13) else (14) add this packet into queue; (15) (19) drop the packet with probability max ; (20) including both packets being served at servers and packets waiting in the buffer, as the system state, we model the system as a Markov Chain with a transition diagram illustrated in Figure 3. Denote the average packet arrival rate as , average service rate of each server is , and the steady probability for state as ; then the equilibrium equation of the system can be presented as follows.…”

Section: Performance Analysis On Congestion Control For Data Transmismentioning

confidence: 99%

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Modeling and Analysis on Congestion Control for Data Transmission in Sensor Clouds

Huang

Duan

et al. 2014

International Journal of Distributed Sensor Networks

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Wireless Sensor Networks (WSNs) and Cloud computing are two emerging technologies, respectively, in the networking and computing fields. Sensor Cloud integrates WSNs and Clouds into an extended form of cloud infrastructure that manages sensors scattered throughout WSNs. Networking plays a crucial role in Cloud computing and becomes a particularly challenging issue in sensor Clouds due to resource limitation of WSNs as the underlying network of the Cloud infrastructure. Therefore, data transmission from sensors to servers in sensor Clouds must be carefully controlled to avoid network congestion. In this paper, we study Random Early Detection-Based (RED-based) congestion control for data transmission in sensor Clouds. Specifically we propose an improved RED (IRED) algorithm that meets sensor Cloud networking requirements better and develop a queueing model coupled with analysis technique to evaluate the performance of the proposed congestion control scheme. We also conduct extensive simulations to evaluate performance of IRED compared with the regular RED algorithm. Our analysis and simulation results demonstrate that the proposed IRED congestion control achieves comparable delay performance and preferable throughput performance in comparison with the standard RED for data transmission in sensor Clouds. The easily implemented control mechanism and low complexity of our proposed algorithm make it more suitable for sensor Clouds.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Model For Red Controlled Data Transmission In Sensormentioning

confidence: 98%