Abstract Recently, the Internet became the most important environment for many activities including sending emails, browsing web sites, making phone calls and even having a videoconference for far education. The incremental growth of the internet traffic leads to a serious problem called congestion. Several Active Queue Management (AQM) algorithms have been implemented at the internet routers to avoid congestion before happening and solve the congestion if it happens by actively controlling the average queue length in the routers. However, most of the developed algorithms handle all the traffics by the same strategy although the internet traffics, real time and non-real time; require different Quality of Service (QoS). This paper presents a new RED-based algorithm, called Dynamic Queue RED (DQRED), to guarantee the required QoS of different traffics. In the proposed algorithm, three queues are used in the internet router; one queue for each traffic type (data, audio and video). The arrived packets are first queued in the corresponding queue. The queued packets are then scheduled dynamically according to the load (the number of queued packets) of each class type. This strategy guarantees QoS for real time applications as well as service fairness.

References

[1] Abdulkareem M., Akil K., Kalakech A., and Kadry S., “EFRED: Enhancement of Fair Random Early Detection Algorithm,” Communications, Network and System Sciences, vol. 8, no. 7, pp. 282-294, 2015.

[2] Adams R., “Active Queue Management: A Survey,” IEEE Communications Surveys and Tutorials, vol. 15, no. 3, pp. 1425-1476, 2013.

[3] Anjum F. and Tassiulas L., “Balanced-RED: An Algorithm to Achieve Fairness in the Internet,” in Proceedings of INFOCOM 8th Annual Joint Conference of the IEEE Computer and Communications Societies, New York, pp. 1-30, 1999.

[4] Attiya G. and El-Khobby H., “Improving Internet Quality of Service through Active Queue Management in Routers,” International Journal of Computer Science Issues, vol. 9, no. 2, pp. 279-286, 2012.

[5] Chitra K. and Padamavathi G., “Classification and Performance of AQM-Based Schemes for Congestion Avoidance,” International Journal of Computer Science and Information Security, vol. 8, no. 1, pp. 331-340, 2010.

[6] Christiansen M., Jeffay K., Ott D., and Smith D., “Tuning RED for Web Traffic,” IEEE/ACM Transactions on Networking, vol. 9, no. 3, pp. 249-264, 2001.

[7] Chung J. and Claypool M., “Dynamic-CBT- Better Performing Active Queue Management for Multimedia Networking,” in Proceedings of in International Workshop on Network and Operating System Support for Digital Audio and Video, Chapel Hill, pp. 1-10, 2000.

[8] Feng W., Kandlur D., Saha D., and Shin D., BLUE: A New Class of Active Queue Management Algorithms, Technical Report CSE-TR-387-99, University of Michigan, 1999.

[9] Flod S., Gummadi R., and Shenker S., “Adaptive RED: An Algorithm for Increasing the Robustness of RED’s Active Queue Management,” in Proceedings of Floyd Adaptive RA, pp. 1-12, 2001.

[10] Floyd S. and Jacobson V., “Link-Sharing and Resource Management Models for Packet Networks,” IEEE/ACM Transactions on Networking, vol. 3, no. 4, pp. 365-386, 1995.

[11] Ghodsi A., Sekar V., Zaharia M., and Stoica I., “Multi-Resource Fair Queueing for Packet Processing,” in Proceedings of the ACM SIGCOMM Conference on Applications, Technologies, Architectures, and Protocols for New Class-based Dynamic Scheduling Strategy for Self-Management ... 481 Computer Communication, Helsinki, pp. 1-12, 2012.

[12] Heckmann O., Piringer M., Schmitt J., and Steinmetz R., How to use Topology Generators to Create Realistic Topologies, KOM Technical Report, Darmstadt University of Technology, 2002.

[13] Ismail A., EL-Sayed A., Elsaghir Z., and Morsi I., “Enhanced Random Early Detection (ENRED),” International Journal of Computer Applications, vol. 92, no. 9, pp. 20-24, 2014.

[14] Jacobson V. and Karels M., “Congestion Avoidance and Control,” in Proceedings of Symposium Proceedings on Communications Architectures and Protocols, vol. 18, no. 4, pp. 314-329, 1988.

[15] Kim W. and Lee B., “FRED- Fair Random Early Detection Algorithm for TCP over ATM Network,” Electronics Letters, vol. 34, no. 2, pp. 152-154, 1998.

[16] McCanne S. and Floyd S., “ns Network Simulator,” http://www.isi.edu/nsnam/ns, Last Visited, 2015.

[17] Meckenney P., “Stochastic Fair Queuing,” in Proceedings of 9th Annual Joint Conference of the IEEE Computer and Communication Societies. The Multiple Facets of Integration, San Francisco, pp. 733-740, 1990.

[18] Ott T., Lakshman T., and Wong L., “SRED: Stabilized RED,” in Proceedings of 8th Annual Joint Conference of the IEEE Computer and Communications Societies, New York, pp. 1346- 1355, 1999.

[19] Rajeswari S. and Venkataramani Y., “Congestion Control and QOS Improvement for AEERG Protocol in MANET,” International Journal on AdHoc Networking Systems, vol. 2, no. 1, pp. 13- 21, 2012.

[20] Seidi M. and Hmadi A., “Enhancing QoS by Using Weighted Fair Queuing Techniques,” International Journal of Advanced Research in Computer Science and Software Engineering, vol. 2, no. 10, pp. 159-163, 2012.

[21] Shreedhar M. and Varghese G., “Efficient Fair Queuing Using Deficit Round Robin,” IEEE/ACM Transactions on Networking, vol. 4, no. 3, pp. 375-385, 1996.

[22] Sivasubramaniam N. and Senniappan P., “Enhanced Core Stateless Fair Queuing with Multiple Queue Priority Scheduler,” The International Arab Journal of Information Technology, vol. 11, no. 2, pp. 159-167, 2014.

[23] Wang H., Liao C., and Tian Z., “Effective Adaptive Virtual Queue: A Stabilising Active Queue Management Algorithm for Improving Responsiveness and Robustness,” IET Communications, vol. 5, no. 1, pp. 99-109, 2011.

[24] Zhou K., Yeung K., and Li V., “Nonlinear RED: A Simple Yet Efficient Active Queue Management Scheme,” Computer Networks, vol. 50, no. 18, pp. 3784-3794, 2006. Hanaa Mohammed graduated in 2000, from the Department of Electronics and Electrical Communications Engineering, Tanta University, Egypt, and she prepare to receive her M.Sc degree this year in computer science and engineering from Faculty of Electronic Engineering, Menoufiya University, Egypt. Her research interests are in the field of computer networks including congestion control, routing, mechanisms for resource management and QoS. Gamal Attiya graduated in 1993 and obtained his M.Sc. degree in computer science and engineering from Menoufia University, Egypt, in 1999. He received PhD degree in computer engineering from University of Marne-La-Vallée, Paris-France, in 2004. He is currently associate professor at Computer Science and Engineering department, Faculty of Electronic Engineering, Menoufia University, Egypt. His main research interests include distributed computing, task allocation and scheduling, cloud computing, Big Data analysis, computer networks and protocols, congestion control, QoS, and multimedia networking. Sami El-dolil received the B. Sc. and M. Sc. degrees in electronic engineering from Menoufia University, Menouf, Egypt, in 1977and 1981, respectively. In 1986 he joined the Communication Research Group at Southampton University, Southampton, England, as a research student doing research on teletraffic analysis for mobile radio communication. He received the Ph. D degree from Menoufia University, Menouf, Egypt, in 1989. He was a Post Doctor Research Fellow at the Department of Electronics and Computer Science, University of Southampton, UK, 1991-1993. From 1994 to 2008 he worked as an Associate Professor, and since 2008 up to now he is working as a professor at the Department of Electronics and Electrical Communication, Faculty of Electronic Engineering, Menoufia University. His current research interests are in High-capacity digital mobile System, and multimedia networks, Telecommunication network spectrum management, planning and optimization.