24.1 Chapter 24 Congestion Control and Quality of Service ICE302 Term # 2 Lecture # 3 Md. Asif Hossain.

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Presentation transcript:

24.1 Chapter 24 Congestion Control and Quality of Service ICE302 Term # 2 Lecture # 3 Md. Asif Hossain

DATA TRAFFIC The main focus of congestion control and quality of service is data traffic. In congestion control we try to avoid traffic congestion. In quality of service, we try to create an appropriate environment for the traffic. So, before talking about congestion control and quality of service, we discuss the data traffic itself.

24.3 Figure 24.1 Traffic descriptors

24.4 Figure 24.2 Three traffic profiles

CONGESTION Congestion in a network may occur if the load on the network—the number of packets sent to the network— is greater than the capacity of the network—the number of packets a network can handle. Congestion control refers to the mechanisms and techniques to control the congestion and keep the load below the capacity.

24.6 In the slow-start algorithm, the size of the congestion window increases exponentially until it reaches a threshold. Note

24.7 In the congestion avoidance algorithm, the size of the congestion window increases additively until congestion is detected. Note

24.8 An implementation reacts to congestion detection in one of the following ways: ❏ If detection is by time-out, a new slow start phase starts. ❏ If detection is by three ACKs, a new congestion avoidance phase starts. Note

24.9 Figure Congestion example Number of transmitted segment Congestion Window size (in segment)

QUALITY OF SERVICE Quality of service (QoS) is an internetworking issue that has been discussed more than defined. We can informally define quality of service as something a flow seeks to attain.

24.11 Figure Flow characteristics

TECHNIQUES TO IMPROVE QoS In Section 24.5 we tried to define QoS in terms of its characteristics. In this section, we discuss some techniques that can be used to improve the quality of service. We briefly discuss four common methods: scheduling, traffic shaping, admission control, and resource reservation.

24.13 Figure FIFO queue

24.14 Figure Priority queuing Starvation  problem

24.15 Figure Weighted fair queuing Round-robin fashion

24.16 Figure Leaky bucket TRAFFIC SHAPING

24.17 Figure Leaky bucket implementation

24.18 A leaky bucket algorithm shapes bursty traffic into fixed-rate traffic by averaging the data rate. It may drop the packets if the bucket is full. Note