Review Article of Research Journal of Mathematics and Computer Science
Traffic Shaping for Congestion Control
Kuyoro Shade O., Okolie Samuel O. and Oyebode Aduragbemi*
Department of Computer Science, Babcock University, Nigeria
The problem of congestion is not new to the field of telecommunications; its root can be traced back to the very foundations of the internet. Most, if not all networks, are currently faced with this problem. The distribution of resources on the network is very vital. The fact that resources are limited brought about major problem such that these limited resources would be shared among various workstations and nodes. As the network grows, and the number of workstations and nodes increases; resources become integral and if not properly managed no meaningful work will be done in such networks. Congestion control, which involved managing resources when the network utilization becomes so high, is of utmost importance so as to avoid congestion collapse. The complex calculations and computation carried out in the existing solutions, increase utilization as well as the problem of congestion. Traffic shaping algorithms provide solutions with little overhead and thus would be preferred to use in medium sized networks. This work proposes traffic shaping as a better solution for congestion control especially in medium size networks.
Keywords: Congestion; Algorithms; Traffic Shaping; Overhead; Networking
How to cite this article:
Kuyoro Shade O., Okolie Samuel O. and Oyebode Aduragbemi. Traffic Shaping for Congestion Control. Research Journal of Mathematics and Computer Science, 2018; 2:10.DOI:10.28933/rjmcs-2018-01-2301
1 Alkharashi, A. (2016). Wireless & Telecommunication. 2nd International Conference and Business Expo . Saudi Arabia: Open Access Jorunal.
2 Cardwell, N., Cheng, Y., Gunn, C. S., Yeganeh, S. H., & Jacobson, V. (2016). Congestion-Based Congestion Control. acmqueue.
3 Hu, X., & Guo, W. (2016). Congestion Control in Wireless Software Defined Networks with Propagation Delay and External Interference: A Robust Control Approach. Hindawi Publishing Corporation.
4 Hussain, M. W., Jamwal, S., & Zaman, M. (2015). Congestion Control Techniques in a Computer Network. International Journal of Computer Applications .
5 Jain, R. (1990). Congestion Control in Computer Networks: Issues and Trends. IEEE.
6 Jayakumari, B., & Senthilkumar, J. (2015). Priority Based Congestion Control Dynamic Clustering Protocol in Mobile Wireless Sensor Networks. Hindawi Publishing Corporation.
7 Jiao, C., Gao, S., Yang, W., Xia, Y., & Zhu, M. (2014). A Fast Heuristic Algorithm for Minimizing Congestion in the MPLS Networks . Scientific Research.
8 Majidi, A., & Mirvaziri, H. (2014). A New Mechanism for Congestion Control in Wireless Multimedia Sensor Networks for Quality of Service and Network Life Time. American Journal of Computing Research Repository.
9 Meenatchi, I., & Palanivel, K. (2014). Intrusion Detection System in MANETS: A Survey . International Journal of Recent Development in Engineering and Technology .
10 Miller, K., & Hsiao, L. (2014). TCPTuner: Congestion Control Your Way . Stanford University Journal.
11 Mohamed, N., Sahib, S., Suryana, N., & Hussin, B. (2016). Understanding Network Congestion Effects On Performance. Journal of Theoretical and Applied Information Technology.
12 Raja, L., & Baboo, S. S. (2014). An Overview of MANET: Applications, Attacks and Challenges. International Journal of Computer Science and Mobile Computing .
13 Rysavy Research. (2014, March 09). LTE Congestion Management. Retrieved from Rysavy Research: . http://www.rysavy.com.
14 Sauter, M. (2011). From GSM to LTE: An Introduction To Mobile Networks and Mobile Broadband. West Sussex: Wiley.
15 Shahzad, F., Mushtaq, M. F., Ullah, S., Siddique, M. A., Khurram, S., & Saher, N. (2015). Improving Queuing System Throughput Using Distributed Mean Value Analysis to Control Network Congestion . Scientific Research.
16 Shar, S. A., Nazir, B., & Khan, I. A. (2016). Comgestiton Control Algorithms in Wireless Sensor Networks. Journal of King Saud University.
17 Sugeng, W., Istiyanto, J. E., Mustofa, K., & Ashari, A. (2015). The Impact of QoS Changes towards Network Performance. International Journal of Computer Networks and Communications Security .
18 Ullah, S., Shahzad, F., Khurram, S., & Anwer, W. (2014). Improving Network Efficiency by Selecting and Modifying Congestion Control Constraints. Scientific Research.
19 Vidyasagar, S., & VidyaShankar, M. (2013). A study on ‘Network Congestion Control Algorithms. Global Research Analysis.
This work and its PDF file(s) are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.