A study of QoS performance of ATM networks
Abstract: The approaches to QoS support of ATM networks are explained, several kinds of schemes such as CBR and ABR, weighted round robin and round robin, ERICA and EFCI are compared. Some simulation work is done and related results are shown and discussed.
1. Introduction
1.1 Problem
Application performance depends on factors such as: hardware, protocols, network design, other users, and the application’s design.
Traditional networks are designed with no traffic differentiation; all traffic – time-critical and non-time-critical is treated equally. Hence, a user transfer a file and a user executing some real time application tasks such as videoconference are treated in the same way. With unlimited bandwidth, this scenario poses no problems. However, as bandwidth becomes increasingly limited, there is a higher degree of contention amongst these applications. In this situation, it becomes important to ensure that time-critical applications do not suffer. A network that can provide different levels service is often said to support quality of service [1].
ATM is well known for providing a rich set of QoS capabilities and in many respects, these schemes are similar to those provided in an IP network, however, the ATM networks have some special features of their own.
1.1 How ATM Works
· ATM network uses fixed-length cells to transmit information. The cell consists of 48 bytes of payload and 5 bytes of header. Transmitting the necessary number of cells per unit time provides the flexibility needed to support variable transmission rates.
· ATM network is connection-oriented. It sets up virtual channel connection (VCC) going through one or more virtual paths (VP) and virtual channels (VC) before transmitting information. The cells is switched according to the VP or VC identifier (VPI/VCI) value in the cell head, which is originally set at the connection setup and is translated into new VPI/VCI value while the cell passes each switch.
· ATM resources such as bandwidth and buffers are shared among users, they are allocated to the user only when they have something to transmit. The bandwidth is allocated according to the application traffic and QoS request at the signaling phase. So the network uses statistical multiplexing to improve the effective throughput.
1.2 ATM QoS parameter
Primary objective of ATM is to provide QoS guarantees while transferring cells across the network. There are mainly three QoS parameters specified for ATM and they are indicators of the performance of the network
· Cell Transfer Delay (CTD):
The delay experienced by a cell between the first bit of the cell is transmitted by the source and the last bit of the cell is received by the destination. This includes propagation delay, processing delay and queuing delays at switches. Maximum Cell Transfer Delay (Max CTD) and Mean Cell Transfer Delay (Mean CTD) are used.
· Peak-to-peak Cell Delay Variation (CDV):
The difference of the maximum and minimum CTD experienced during the connection. Peak-to-peak CDV and Instantaneous CDV are used.
· Cell Loss Ratio (CLR):
The percentage of cells lost in the network due to error or congestion that are not received by the destination. CLR value is negotiated between user and network during call set up process and is usually in the range of 10-1 to 10-15.
1.4 ATM Traffic Descriptors
The ability of a network to guarantee QoS depends on the way in which the source generates cells (Uniformly or in a bursty way) and also on the availability of network resources for e.g. buffers and bandwidth. The connection contract between user and network will thus contain information about the way in which traffic will be generated by the source. A set of traffic descriptors is specified for this purpose. Policing algorithms check to see if the source abides by the traffic contract. The network only provide the QoS for the cells that do not violate these specifications.
The following are traffic descriptors specified for an ATM network.
· Peak Cell Rate (PCR):
The maximum instantaneous rate at which the user will transmit.
· Sustained Cell Rate (SCR):
The average rate as measured over a long interval.
· Burst Tolerance (BT):
The maximum burst size that can be sent at the peak rate.
· Maximum Burst Size (MBS):
The maximum number of back-to-back cells that can be sent at the peak cell rate.
· Minimum Cell Rate (MCR):
The minimum cell rate desired by a user.
1.5 ATM Service Categories
Providing desired QoS for different applications is very complex. For example, voice is delay-sensitive but not loss-sensitive, data is loss- sensitive but not delay-sensitive, while some other applications may be both delay-sensitive and loss-sensitive.
To make it easier to manage, the traffic in ATM is divided into five service classes accorcing to various combination requested QoS:
· CBR: Constant Bit Rate
CBR is the service category for traffic with rigorous timing requirements like voice, and certain types of video. CBR traffic needs a constant cell transmission rate throughout the duration of the connection.
· rt-VBR: Real-Time Variable Bit Rate
This is intended for variable bit rate traffic for e.g. certain types of video with stringent timing requirements.
· nrt-VBR: Non-Real-Time Variable Bit Rate
This is for bursty sources such as data transfer, which do not have strict time or delay requirements.
· UBR: Unspecified Bit Rate
This is ATM’s best-effort service, which does not provide any QoS guarantees. This is suitable for non-critical applications that can tolerate or quickly adjust to loss of cells.
· ABR: Available Bit Rate
ABR is commonly used for data transmissions that require a guaranteed QoS, such as low probability of loss and error. Small delay is also required for some application, but is not as strict as the requirement of loss and error. Due to the burstiness, unpredictability and huge amount of the data traffic, sources implement a congestion control algorithm to adjust their rate of cell generation. Connections that adjust their rate in response to feedback may expect a lower CLR and a fair share of available bandwidth.
The available bandwidth at an ABR source at any point of time is dependant on how much bandwidth is remaining after the CBR and VBR traffic have been allocated their share of bandwidth. Figure 1 explains this concept.
1.6 ATM QoS Priority Scheme
Each service category in ATM has its own queue. There are mainly two schemes for queue service. In round-robin scheme, all queues have the same priority and therefore have the same chance of being serviced. The link’s bandwidth is equally divided amongst the queues being serviced. Another scheme is weighted round-robin scheme, which is somehow similar to WFQ in IP networks: queues are serviced depending on the weights assigned to them. Weights are determined according to the Minimum Guaranteed Bandwidth attribute of each queue parameter in each ATM switch. This scheme ensures that the guaranteed bandwidth is reserved for important application such as CBR service category.
1.7 ATM Congestion control
Due to the unpredictable traffic pattern, congestion is unavoidable. When the total input rate is greater than the output link capacity, congestion happens. Under a congestion situation, the queue length may become very large in a short time, resulting in buffer overflow and cell loss. So congestion control is necessary to ensure that users get the negotiated QoS.
In this study, two major congestion algorithms are focused, which are especially for ABR source. Binary Feedback scheme (EFCI) uses a bit to indicate congestion occurs. A switch may detect congestion in the link if the queue level exceeds a certain level. Accordingly, the switch sets the congestion bit to 1. When the destination receives these data cells with EFCI bit set to 1, the destination sets the CI bit of the backward RM cell to 1 indicating congestion occurs. When the source receives a backward RM cell with CI bit as 1, the source has to decrease its rate. The EFCI only told the source increase or decrease the rate and hence the method converges slowly. The Explicit Rate Indication for Congestion Avoidance (ERICA) algorithm solves the problem by allowing each switch to explicitly tell the desired rate to the passing RM cells, the source adjusts the rate according to the backward RM cells.
2. Simulation
2.1 simulation Tools
Optimized Network Engineering Tools (OPNET) is the simulation tool used in this study. OPNET has many attractive features and can simulate large communication networks with detailed protocol modeling and performance analysis [2].
2.2 Network
Figure 2 shows an ATM network used in the project to study the ATM network. The network consists of servers, workstations and ATM switches, they are connected by OC3 links that can sustain 155.52Mbps traffic, the ATM switching speed is infinity, and the VC lookup delay is 1E-10, the hence the network capacity is about 150Mbps. Three kinds of traffic are generated by three applications, which are voice, video conference, and Ftp. Voice is run on AAL2 layer, while video conference and ftp are run on AAL5 layer. Voice and video are sensitive to the timeliness, so I arbitrarily define voice use CBR service, video use rt_VBR service, data uses ABR service. The voice traffic is originally around 4Mbps, and the other two are around 3Mbps.
Figure 3 shows a larger ATM network that is also used in the project. The traffic in this network is generated by ATM_uni_src model, so the traffic generated is ideal--that is no burst occurs. There are also three kinds of traffic voice, video and data. Because the traffic is stable, their ratio can be accurately set as 4: 3: 3. This network model is only used to study in large network, when traffic scales, the behavior of the network for each kind of service category, and the simulation speed is faster than that traffic pattern generated by real application in network1.
The QoS of each service category is defined in table1.
Table1
CBR / RT_VBR / ABRppCDV(msec) / 5microsec / 10microsec / 20microsec
maxCTD(msec) / 15microsec / 15microsec / 3millisec
CLR / 3.00E-07 / 3.00E-07 / 1.00E-05
2.3 Simulation results and discussion
2.3.1 Load and throughput
Four sceneries are run on network 2, they differ in traffic size. The total traffic generated with each scenery and the result collected are listed in table 2.
Table 2: The result of Network 2
Traffic size / 20M / 100M / 120M / 150MStatistic / Average / Maximum / Average / Maximum / Average / Maximum / Average / Maximum
ATM ABR Cell Delay (sec) / 1.8 / 3.56 / 0.078 / 0.154 / 0.078 / 0.155 / 0.078 / 0.154
ATM ABR Cell Delay Variation / 0.37 / 1.08 / 0.00066 / 0.00194 / 0.00067 / 0.00198 / 0.00066 / 0.00195
ATM ABR Cell Loss Ratio / 0 / 0 / 0 / 0 / 0 / 0 / 0 / 0
ATM Call Blocking Ratio (%) / 0 / 0 / 0 / 0 / 0 / 0 / 0 / 0
ATM CBR Cell Delay (sec) / 0.00164 / 0.00164 / 0.00164 / 0.00164 / 0.00164 / 0.00164 / 0.0016 / 0.0016
ATM CBR Cell Delay Variation / 0 / 0 / 0 / 0 / 0 / 0 / 0 / 0
ATM CBR Cell Loss Ratio / 0 / 0 / 0 / 0 / 0 / 0 / 0 / 0
ATM Cell Delay (sec) / 0.52 / 1.03 / 0.024 / 0.0463 / 0.0301 / 0.0586 / 0.0247 / 0.0476
ATM Cell Delay Variation / 0.25 / 1.02 / 0.00019 / 0.00178 / 0.00027 / 0.00198 / 0.00014 / 0.00145
ATM Global Throughput (bits/sec) / 18,218,711 / 18,252,000 / 88,332,000 / 92,300,000 / 103,970,000 / 108,600,000 / 128,052,000 / 133,800,000
ATM Load (bits) / 1,000 / 1,000 / 5,000 / 5,000 / 5,000 / 5,000 / 5,000 / 5,000
ATM Load (bits/sec) / 19,976,307 / 20,012,333 / 95,993,000 / 100,200,000 / 115,248,000 / 120,300,000 / 139,223,000 / 145,500,000
ATM RT_VBR Cell Delay (sec) / 0.00125 / 0.00125 / 0.00106 / 0.00106 / 0.00125 / 0.00125 / 0.00106 / 0.00106
ATM RT_VBR Cell Delay Variation / 0 / 0 / 0 / 0 / 0 / 0 / 0 / 0
ATM RT_VBR Cell Loss Ratio / 0 / 0 / 0 / 0 / 0 / 0 / 0 / 0
The simulations only run 10 seconds because the memory of my computer is not large enough, and the speed is very slow. Since the traffic is generated in bunch, it is difficult to scale the traffic size, because when the traffic increases, if it exceeds the capacity of network, the request is rejected; therefore, the load is hard to exceed 150Mbps. Because no network overload is simulated, the throughput increases with the load. Ideally, the throughput should be increase with increased load and become static under infinite load. The latency and jitter is very small, this is because congestions do not occur because of the sable traffic and the QoS is guaranteed for each service. From the table, it can be seen that the cell delay for ABR service is largest amongst the three categories, this result is consist with what we expected.
2.3.2 Comparison of ERICA vs EFCI algorithms
ERICA and EFCI are methods used in congestion control for ABR service, in this study, is the FTP application.
Two scenarios are run based on network 1. The scenario 23 uses ERICA algorithm, while the scenario 24 uses EFCI algorithm in ATM switches.