Using Random Early Detection for Enhancing Network Performance by Adjusting Lower Thresholds and Average Queue Sizes

Deadlock, Active queue management, RED, Average queue size

Authors

  • Nghiem Van Tinh Thai Nguyen University of Technology, Thai Nguyen University Thai Nguyen, Vietnam
  • Pham Quang Hieu Thai Nguyen University of Technology, Thai Nguyen University Thai Nguyen, Vietnam
  • Dao Ngoc Ton Thai Nguyen University of Technology, Thai Nguyen University Thai Nguyen, Vietnam
January 3, 2023
January 3, 2023

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In internet media, the created information will move to network nodes called the routing information, from one node to another based on the request made. When data loads increase in communication links, routers must be designed to supply reasonable data flow from resource to its target, to all network nodes. In case accessed data is heavy, routers can be deadlocked and reduce router's bandwidth which leads to increase packet loss. In order to sustainably transmit packets through such routers, they need to be designed and provided with effective deadlock avoidance algorithms. Formerly, these algorithms were used as Active queue management-AQM, Drop Tail algorithm (DT), and Random Early Detection-RED. This study suggests an innovative RED named  LtRED (Lower threshold of RED) to address RED's shortcomings. Research results evaluated on NS2 showed the innovation LtRED algorithm was better than RED in terms of packet loss rate, average queue delay, and average throughput.