الفهرس 
Chapter 1 IntroductionOnly 14 pages are availabe for public view
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Abstract
As the internet is expected to better support many applications such as multimedia with limit bandwidth, new mechanisms are needed to control the congestion in the network.
Generally, there are two ways to implement congestion control: (1) Network assistant congestion controls; they are approach taken by routers. These approaches use the router queue size to monitor the congestion state of the network. (2) End-to-End congestion controls; they are approaches taken by the transmission control protocol (TCP) and are mostly achieved in transport layer.
Active Queue Management (AQM) algorithms play an important role to ensure the stability of the Internet. Random Early Detection (RED) is the first active queue management algorithm proposed for deployment in TCP/IP networks. RED algorithm is designed to avoid congestion, global synchronization, and avoidance of bias against traffic and bound on average queue length to limit delay.
RED has its own variants such as: Adaptive RED (ARED), Stabilized RED (SRED), Flow RED (FRED), Dynamic RED (DRED) and Modified RED (ModRED). RED variants tends to overcome its drawbacks (i.e., RED doesn’t store any state information about any flow), and control average queuing delay, while still maintaining high link utilization, reducing packet drops, reducing global synchronization and burst connection. All RED variants depend on RED parameters in dealing with congestion.
RED has some parameters tuning issues that need to be carefully addressed for it to give good performance under different network scenarios. The proposed algorithm called Enhanced Random Early Detection (ENRED). ENRED works to improve these parameters to provide better congestion control over the network while remaining the advantage of RED. This thesis will introduce ENRED and some features about RED and its variants. The proposed algorithm (ENRED) simulate by using the well-known network simulator ns-2, by comparing it to the original RED. Simulation results show that the proposed algorithm achieves better queue size than RED and decreases the delay and losses.