4. Design and Simulation

The main focus of this thesis is to investigate the Quality of Service of an Ethernet network based on packet size. An experimental setup is configured and designed with 8 experimental scenarios. The Riverbed network simulator is used to observe the network behavior upon different packet sizes. The simulation results from Riverbed simulator are very close to real life scenarios and provide high level Ethernet network development features.

Ethernet LAN was designed for the low cost, flexibility in installation and decentralized IP packet transmissions among 265 hosts upto 3 Mbps capacity [19] . Today a Fast Ethernet type is used for high throughput host that can provide 10 Gbps full-duplex collision free link. In order to analyze the effect of packet size on QoS in Ethernet network, an experimental Ethernet LAN environment is established having 16 workstations, two hubs and a switch, illustrated in Figure 1(a). Each of the two hubs is connected with eight workstations by a full duplex link. The switch is connected with the hubs by a full duplex link. All the devices are connected though a link of bandwidth 10 Mbps. The client machine is configured using Microsoft Windows 7 and it is preferred as its one of the most popular and widely used operating systems [20] . We created 7 scenarios to carry out the experiment varying the packet sizes (128 Bytes, 256 Bytes, 512 Bytes, 1024 Bytes and 2048 Bytes). When a packet size exceeds maximum transmission unit of Ethernet network of 1518 Bytes we segmented the packet. Packet size for 8 different scenarios is given below Table 1.

The traffic generation parameters and Ethernet parameters for all the scenarios are same. They are presented in Tables 2-4 in the following.

Table 1. Packet generation parameters for different scenarios.

Table 2. Traffic generation parameters.

Table 3. Ethernet parameters.

Table 4. Link parameters.

5. Simulation Results

This section offers competitive description and the analysis of the obtained discrete event simulation result. The result is based on the packet size in the Ethernet network observing its performance analysis. The graphs are generated using different Quality of service parameters (Packet loss ratio, Throughput, Queuing delay, Bit error rate, Delay etc.).

5.1. Throughput

Throughput is considered as one of the vital QoS parameters for networks [21] . Higher throughput is always expected. In general terms; throughput is the rate of production or the rate at which something can be processed. The simulation result shows the highest throughput with larger packet sizes near to 1024 Bytes (Figure 2).

5.2. Delay

The network delay specifies how long it takes for a bit of data to travel across the network from one node or endpoint to another. It is typically measured in multiples or fractions of seconds. Low network delay is essential for better network performance. Figure 3 illustrates the Ethernet network delay for different packet size. We can see that delay is proportion to packet size. This means small packet size, low delay and higher packet Sizes produce higher delay.

5.3. Packet Loss Ratio

The QoS of an Ethernet largely depends on the network performance parameter packet loss ratio. Large packet loss ratio degrades a network performance. As large number of packet losses increasing the retransmission, which fall down the network performance. Packet loss ratio is described as the ratio of lost packet and the total packet per unit of time. Number of lost packet/(Number of lost packet + Number of packets received successfully). Low packet loss ratio is always expected for better QoS performance. Figure 4 presents the simulation result of packet loss ratio for 128, 256, 512 and 1024 Bytes packets.

5.4. Queuing Delay

Queuing delay represents the queuing delay that packets from the network layer incur at the MAC queue until it can be executed [22] . It is the main component of overall network delay. Model has huge queuing delay for large packet size. Less queuing delay is expected to avoid performance degradation of an Ethernet network.

5.5. Bit Error Per Packet

This QoS parameter represents the average number of bit errors ina packet sent over a channel [23] . Bit error per packet plays a vital role for QoS of an Ethernet network. The Less bit error per packet improves the network performance. Hence, less bit error per packet is expected. Figure 5 illustrates the result of bit error per packet based on packet size. Figure 6 shows that in 128 Bytes packet size, bit error per packet are 0 and bit errors per packet increases with the increase of packet size.

5.6. Traffic Forwards

Amount of traffic forwarded per unit of time. Figure 7 shows that when packet size exceeds the MTU then no traffic, forwards form switches which means all packets are dropped.

5.7. Throughput for Segmented Packets

In general terms; throughput is the rate of production or the rate at which something can be processed. When

Figure 2. Throughput (bits/sec) at switch.

Figure 3. Network delay (sec) for 128, 256, 512 and 1024 Bytes packet size.

Figure 4. Packet loss ratio for 128, 256, 512 and 1024 Bytes packet size.

used in the context of communication networks, such as Ethernet, throughput or network throughput is the rate of successful message delivery over a communication channel. Throughput is considered as one of the most important QoS parameters for networks. Higher throughput is always expected. Figure 8 illustrates the throughput when packet size exceeds MTU and hence segmentation is needed [24] . For 2048 Byte packet size two different segmentation sizes (1500 Bytes and 1024 Bytes) were used for Scenario 6 and Scenario 7 respectively. The simulation result shows that throughput for segmentation, size The simulation result shows the higher throughput with larger packet sizes near to 1024 bytes. Bytes and 1024 Bytes is almost same for the Ethernet network.

Figure 5. Bit error per packet for 128, 256, 512 and 1024 Byte packet size.

Figure 6. Queuing delay (sec) for 128, 256, 512 and 1024 Bytes packet size.

Figure 7. Traffic forwarded (bits/sec) when packet size exceeds MTU.

Figure 8. Throughput (bits/sec) for 1024 and 1500 Bytes segmentation size when packet size is 2048 Bytes.

6. Conclusions

The simulation presents a set of observations regarding impact of different packet sizes on the QoS in Ethernet local area network. Several QoS parameters came out with distinctive increase or decrease in performance. Segmentation is applied in the larger packet size of the Ethernet network. The simulation result represents that, for larger size packets than MTU of the network, throughput increases in a large amount implying better QoS for packet transmitted within the network. Meanwhile, for the larger packets no traffic forwarded from the switch. End-to-end delay increases exponentially for larger packets which drastically increases the queueing delay, packet loss ratio and error rate as well. This highly indicates that higher packet size gives inefficient QoS and less performance of the Ethernet network than the smaller packet’s. Though there is a slightly better performance in highly increased throughput, however, the overall network performance degrades as most of the QoS parameters decreases for larger packet sizes than MTU in this testbed.

The future aspects of this performance fluctuation and findings can give a downbeat view on the QoS of the wireless environment for varying packet sizes. Segmentation of higher packet size can be a promising area to analyze the vastly used ZigBee network. Effect of packet size of Mobility network and VoIP application can be analyzed because the demand for such application is largely increasing day by day.


*Corresponding author.

Cite this paper
Islam, N. , Bawn, C. , Hasan, J. , Swapna, A. and Rahman, M. (2016) Quality of Service Analysis of Ethernet Network Based on Packet Size. Journal of Computer and Communications, 4, 63-72. doi: 10.4236/jcc.2016.44006.

[1]   Beyranvand, H., Martin, L., Martin, M. and Salehi, J.A. (2015) FiWi Enhanced LTE-A HetNets with Unreliable Fiber Backhaul Sharing and WiFi Offloading. IEEE Conference on Computer Communications (INFOCOM), Kowloon, April 26 2015-May 1 2015, 1275-1283.

[2]   Carmo, M., Sá Silva, J., Monteiro, E., Sim?es, P. and Boavida, F. (2005) Ethernet QoS Modeling in Emerging Scenarios. Proceedings of 3rd International Workshop on Internet Performance, Simulation, Monitoring and Measurement (IPS-MoMe 2005), Warsaw, 14-15 March 2005, 90-96.

[3]   Salsano, S., Detti, A., Cancellieri, M., Pomposini, M. and Blefari-Melazzi, N. (2012) Transport-Layer Issues in Information Centric Networks. Proceedings of the Second Edition of the ICN Workshop on Information-Centric Networking, Helsinki, 17 August 2012, 19-24.

[4]   Li, Y., Qi, X., Keally, M., Ren, Z., Zhou, G., Xiao, D. and Deng, S. (2013) Communication Energy Modeling and Optimization through Joint Packet Size Analysis of BSN and WiFi Networks. IEEE Transactions on Parallel and Distributed Systems, 24, 1741-1751.

[5]   Braun, T., Diaz, M., Gabeiras, J.E. and Staub, T. (2008) End-to-End Quality of Service over Heterogeneous Networks. Springer Science & Business Media.

[6]   Das, R., Jain, V., Krishnan, U. and Venkatsubra, V. (2013) Efficient Path Maximum Transmission Unit Information Discovery and Storage. U.S. Patent No. 8,422,501.

[7]   Gao, Y., Dai, L. and Hei, X. (2015) Throughput Optimization of Non-Real-Time Flows with Delay Guarantee of Real-Time Flows in WLANs. IEEE International Conference on Communications (ICC), London, 8-12 June 2015, 1541-1546.

[8]   Chitre, M., Motani, M. and Shahabudeen, S. (2012) Throughput of Networks with Large Propagation Delays. IEEE Journal of Oceanic Engineering, 37, 645-658.

[9]   Wang, X.D., Yin, J. and Agrawal, D.P. (2005) Effects of Contention Window and Packet Size on the Energy Efficiency of Wireless Local Area Network. IEEE Wireless Communications and Networking Conference, 1, 94-99.

[10]   Tauber, M., Bhatti, S.N. and Yu, Y. (2011) Application Level Energy and Performance Measurements in a Wireless LAN. IEEE/ACM International Conference on Green Computing and Communications (GreenCom), Sichuan, 4-5 August 2011, 100-109.

[11]   Hussain, I., Ahmed, Z.I., Saikia, D.K. and Sarma, N. (2015) A QoS-Aware Dynamic Bandwidth Allocation Scheme for Multi-Hop WiFi-Based Long Distance Networks. EURASIP Journal on Wireless Communications and Networking, 1, 1-18.

[12]   Srikant, R. (2012) The Mathematics of Internet Congestion Control. Springer Science & Business Media, Berlin, Heidelberg.

[13]   K?hnen, C., überall, C., Rajarajan, M., J?ger, R. and Rako?evi?, V. (2015) Autonomous QoS Management and Policing in Unmanaged Local Area Networks. Journal of Computer Networks and Communications, 2015, 1-24.

[14]   Hassani, V., Talebi, H.A., Shafiee, M. and Taheri, H. (2007) Timing Analysis and Response Time of End to End Packet Delivery in Switched Ethernet Network. European Control Conference (ECC), Kos, 2-5 July 2007, 31-37.

[15]   Yazid, M., Bouallouche-Medjkoune, L., A?ssani, D. and Ziane-Khodja, L. (2013) Analytical Analysis of Applying Packet Fragmentation Mechanism on IEEE 802.11b DCF Network in Non Ideal Channel with Infinite Load Conditions. Wireless Networks, 20, 917-934.

[16]   Modeler (2015) Riverbed Technology.

[17]   Lu, Z. and Yang, H.J. (2012) Unlocking the Power of OPNET Modeler. Cambridge University Press, Cambridge.

[18]   Ghassemlooy, Z., Le Minh, H., Rajbhandari, S., Perez, J. and Ijaz, M. (2012) Performance Analysis of Ethernet/ Fast-Ethernet Free Space Optical Communications in a Controlled Weak Turbulence Condition. Journal of Lightwave Technology, 30, 2188-2194.

[19]   Kiravuo, T., Sarela, M. and Manner, J. (2013) A Survey of Ethernet LAN Security. IEEE Communications Surveys & Tutorials, 15, 1477-1491.

[20]   Hanay, Y.S., Li, W., Tessier, R. and Wolf, T. (2012) Saving Energy and Improving TCP Throughput with Rate Adaptation in Ethernet. IEEE International Conference on Communications (ICC), Ottawa, 10-15 June 2012, 1249-1254.

[21]   Queck, R. (2012) Analysis of Ethernet AVB for Automotive Networks Using Network Calculus. IEEE International Conference on Vehicular Electronics and Safety (ICVES), Istanbul, 24-27 July 2012, 61-67.

[22]   Haigh, P.A., et al. (2012) Development of a Visible Light Communications System for Optical Wireless Local Area Networks. Computing, Communications and Applications Conference (ComComAp), Hong Kong, 11-13 January 2012, 351-355.

[23]   Valcarenghi, L., Van, D.P., Raponi, P.G., Castoldi, P., Campelo, D.R., Wong, S.W., Yen, S.H., Kazovsky, L.G. and Yamashita, S. (2012) Energy Efficiency in Passive Optical Networks: Where, When, and How? IEEE Network, 26, 61-68.

[24]   Hua, B., Hua, H.L. and Xiong, W. (2012) Changing Ethernet MTU Size on Demand with No Data Loss. U.S. Patent No. 8,214,535.