rates and interarrival periods much more predictable. Class-Based WFQ: Ensuring Network Bandwidth
CBWFQ is one of Cisco's newest congestion-management tools for providing greater flexibility. It will provide a minimum amount of bandwidth to a class as opposed to providing a maximum amount of bandwidth as with traffic shaping. CBWFQ allows a network administrator to create minimum guaranteed bandwidth classes. Instead of providing a queue for each individual flow, the administrator defines a class that consists of one or more flows, each class with a guaranteed minimum amount of bandwidth. CBWFQ prevents multiple low-priority flows from swamping out a single high-priority flow. For example, WFQ will provide a video stream that needs half the bandwidth of T1 if there are two flows. But, if more flows are added, the video stream gets less of the bandwidth because WFQ's mechanism creates fairness. If there are 10 flows, the video stream will get only 1/10th of the bandwidth, which is not enough. CBWFQ provides the mechanism needed to provide the half of the bandwidth that video needs. The network administrator defines a class, places the video stream in the class, and tells the router to provide 768 kbps (half of a T1) service for the class. Video therefore gets the bandwidth that it needs. The rest of flows receive a default class. The default class uses flow-based WFQ schemes fairly allocating the remainder of the bandwidth (half of the T1, in this example).
Content 3.2 Implementing Cisco IOS QoS 3.2.3 Queue Management (Congestion-Avoidance Tools) Congestion avoidance is a form of queue management. Congestion-avoidance techniques monitor network traffic loads in an effort to anticipate and avoid congestion at common network bottlenecks, as opposed to congestion-management techniques that operate to control congestion after it occurs. The primary Cisco IOS congestion avoidance tool is WRED. The random early detection (RED) algorithms avoid congestion in internetworks before it becomes a problem. RED works by monitoring traffic load at points in the network and randomly discards packets if the congestion begins to increase. The result of the drop is that the source detects the dropped traffic and slows its transmission. RED is primarily designed to work with TCP in IP internetwork environments. WRED combines the capabilities of the RED algorithm with IP precedence. This combination provides for preferential traffic handling for higher-priority packets. It can selectively discard lower-priority traffic when the interface starts to get congested and can provide differentiated performance characteristics for different classes of service as shown in Figure . WRED is also Resource Reservation Protocol (RSVP) aware and can provide an integrated services controlled-load QoS. As you know, each queue can house a finite number of packets. A full queue causes tail drops. Tail drops are dropped packets that could not fit into the queue because the queue was full. This is undesirable because the dropped packet may have been a high-priority packet and the router did not have a chance to queue it. If the queue is not full, the router can look at the priority of all arriving packets and drop the lower-priority packets, allowing high-priority packets into the queue. By managing the depth of the queue (the number of packets in the queue) by dropping specified packets, the router does its best to make sure that the queue does not fill and that tail drops do not happen. This allows the router to make a better decision as to which packets to drop when the queue depth increases. WRED also helps prevent overall congestion in an internetwork. WRED uses a minimum threshold for each IP precedence level to determine when to drop a packet. (The queue length must exceed the minimum threshold for WRED to consider a packet as a candidate for dropping.) Consider this example for two classes of traffic. The first class has a minimum drop threshold for IP precedence of 20. The next queue in our example has a drop threshold for IP precedence of 22. If the queue length is 21, then WRED drops packets for the first class, but packets from the second class remain in the queue. If the queue depth deepens and exceeds 22, then packets with IP precedence = 1 can be dropped as well. WRED uses an algorithm that raises the probability that the router can drop a packet as the queue depth rises from the minimum drop threshold to the maximum drop threshold. Above the maximum drop threshold, WRED drops all packets.
Content 3.2 Implementing Cisco IOS QoS 3.2.4 Preparing to Implement QoS There are three basic steps shown in Figure involved in implementing QoS on a network: Step 1 Identify types of traffic and their requirements: Study the network to determine the type of traffic that is running on the network and then determine the QoS requirements needed for the different types of traffic. Step 2 Define traffic classes: This activity groups the traffic with similar QoS requirements into classes. For example, three classes of traffic might be defined as voice, mission-critical, and best effort. Step 3 Define QoS policies: QoS policies meet QoS requirements for each traffic class.
Content 3.2 Implementing Cisco IOS QoS 3.2.5 Step 1: Identify Types of Traffic and Their Requirements The first step in implementing QoS is to identify the traffic on the network and then determine the QoS requirements and the importance of the various traffic types. This step provides some high-level guidelines for implementing QoS in networks that support for multiple applications, including delay-sensitive and bandwidth-intensive applications. These applications may enhance business processes, but stretch network resources. QoS can provide secure, predictable, measurable, and guaranteed services to these applications by managing delay, delay variation (jitter), bandwidth, and packet loss in a network. This step consists of these activities illustrated in Figure : Determining which applications are business-critical and necessitate protection requires you to review all of the applications competing for network resources. Tools to analyze the traffic patterns in the network include NetFlow Accounting, Network-based Application Recognition (NBAR), and QoS Device Manager (QDM).