Quality of Service (QoS) generally refers to measurable like latency and throughput, things that directly affect the user experience. Queuing (the most popular QoS tool) involves choosing the packets to be sent based ...Quality of Service (QoS) generally refers to measurable like latency and throughput, things that directly affect the user experience. Queuing (the most popular QoS tool) involves choosing the packets to be sent based on something other than arrival time. The Active queue management is important subject to manage this queue to increase the effectiveness of Transmission Control Protocol networks. Active queue management (AQM) is an effective means to enhance congestion control, and to achieve trade-off between link utilization and delay. The de facto standard, Random Early Detection (RED), and many of its variants employ queue length as a congestion indicator to trigger packet dropping. One of these enhancements of RED is FRED or Fair Random Early Detection attempts to deal with a fundamental aspect of RED in that it imposes the same loss rate on all flows, regardless of their bandwidths. FRED also uses per-flow active accounting, and tracks the state of active flows. FRED protects fragile flows by deterministically accepting flows from low bandwidth connections and fixes several shortcomings of RED by computing queue length during both arrival and departure of the packet. Unlike FRED, we propose a new scheme that used hazard rate estimated packet dropping function in FRED. We call this new scheme Enhancement Fair Random Early Detection. The key idea is that, with EFRED Scheme change packet dropping function, to get packet dropping less than RED and other AQM algorithms like ARED, REM, RED, etc. Simulations demonstrate that EFRED achieves a more stable throughput and performs better than current active queue management algorithms due to decrease the packets loss percentage and lowest in queuing delay, end to end delay and delay variation (JITTER).展开更多
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...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.展开更多
为了提高响应流和非响应流之间的公平性,提出了一种基于速率公平的RED改进算法——RF-RED(ratefairness random early detection).该算法在路由器端计算UDP流的平均速率并与TCP友好流速率进行比较,根据比较结果动态调整UDP流和TCP流的...为了提高响应流和非响应流之间的公平性,提出了一种基于速率公平的RED改进算法——RF-RED(ratefairness random early detection).该算法在路由器端计算UDP流的平均速率并与TCP友好流速率进行比较,根据比较结果动态调整UDP流和TCP流的最大丢包率,最后使用RED算法分别更新UDP流和TCP流的实际丢包率.通过使用RF-RED算法,UDP流在瓶颈链路上成为TCP友好流,同时瓶颈带宽得到了公平利用.仿真结果验证了该算法的有效性.展开更多
拥塞控制(congestion control)机制是确保InternetQoS的关键因素,随机早期检测(Random Early D etection,RED)算法是提高网络服务质量、解决网络阻塞的重要算法。针对网关的到达队列来说,丢包率的算法采用RED基本思想中与平均队列长度...拥塞控制(congestion control)机制是确保InternetQoS的关键因素,随机早期检测(Random Early D etection,RED)算法是提高网络服务质量、解决网络阻塞的重要算法。针对网关的到达队列来说,丢包率的算法采用RED基本思想中与平均队列长度呈线性的关系并不合适,提出了立方RED算法。算法对RED算法进行了改进,使流丢包率与平均队列长度呈立方函数关系,通过NS-2仿真软件研究表明,算法可以有效的增加了网关的吞吐量、减少丢包率。展开更多
文摘Quality of Service (QoS) generally refers to measurable like latency and throughput, things that directly affect the user experience. Queuing (the most popular QoS tool) involves choosing the packets to be sent based on something other than arrival time. The Active queue management is important subject to manage this queue to increase the effectiveness of Transmission Control Protocol networks. Active queue management (AQM) is an effective means to enhance congestion control, and to achieve trade-off between link utilization and delay. The de facto standard, Random Early Detection (RED), and many of its variants employ queue length as a congestion indicator to trigger packet dropping. One of these enhancements of RED is FRED or Fair Random Early Detection attempts to deal with a fundamental aspect of RED in that it imposes the same loss rate on all flows, regardless of their bandwidths. FRED also uses per-flow active accounting, and tracks the state of active flows. FRED protects fragile flows by deterministically accepting flows from low bandwidth connections and fixes several shortcomings of RED by computing queue length during both arrival and departure of the packet. Unlike FRED, we propose a new scheme that used hazard rate estimated packet dropping function in FRED. We call this new scheme Enhancement Fair Random Early Detection. The key idea is that, with EFRED Scheme change packet dropping function, to get packet dropping less than RED and other AQM algorithms like ARED, REM, RED, etc. Simulations demonstrate that EFRED achieves a more stable throughput and performs better than current active queue management algorithms due to decrease the packets loss percentage and lowest in queuing delay, end to end delay and delay variation (JITTER).
文摘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.
文摘为了提高响应流和非响应流之间的公平性,提出了一种基于速率公平的RED改进算法——RF-RED(ratefairness random early detection).该算法在路由器端计算UDP流的平均速率并与TCP友好流速率进行比较,根据比较结果动态调整UDP流和TCP流的最大丢包率,最后使用RED算法分别更新UDP流和TCP流的实际丢包率.通过使用RF-RED算法,UDP流在瓶颈链路上成为TCP友好流,同时瓶颈带宽得到了公平利用.仿真结果验证了该算法的有效性.
文摘拥塞控制(congestion control)机制是确保InternetQoS的关键因素,随机早期检测(Random Early D etection,RED)算法是提高网络服务质量、解决网络阻塞的重要算法。针对网关的到达队列来说,丢包率的算法采用RED基本思想中与平均队列长度呈线性的关系并不合适,提出了立方RED算法。算法对RED算法进行了改进,使流丢包率与平均队列长度呈立方函数关系,通过NS-2仿真软件研究表明,算法可以有效的增加了网关的吞吐量、减少丢包率。
