International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

Congestion Aware Packet Routing For Delay Sensitive Cloud Communications

Author NameAuthor Details

Vincent O. Nyangaresi, Silvance O. Abeka, Solomon. O. Ogara

Vincent O. Nyangaresi[1]

Silvance O. Abeka[2]

Solomon. O. Ogara[3]

[1]Informatics and Innovtive Systems, Jaramogi Oginga Odinga University of Science & Technology, Kenya

[2]Informatics and Innovtive Systems, Jaramogi Oginga Odinga University of Science & Technology, Kenya

[3]Informatics and Innovtive Systems, Jaramogi Oginga Odinga University of Science & Technology, Kenya

Abstract

In the recent years, many organizations have turned to cloud technology to support their information technology services. The cloud servers are therefore increasingly holding huge and sensitive information belonging to diverse groups of individuals and companies. Additionally, some organizations employ the cloud to provide them with online backup services. One of the most outstanding requirements for cloud customers is availability – the customers must be able to access their information and other resources stored in the cloud any time and from anywhere on the globe. This means that there should be efficient network design such that any delays are averted. The connection between the customer and the cloud can therefore be regarded as delay senstive. Network congestions often lead to delays and packet losses. Transmission control protocol employs four congestion control algorithms – slow start, congestion avoidance, fast retransmit and fast recovery, all of which fail to meet the requirements of delay intolerance. Transmission control protocol pacing has been suggested as a possible solution to delays and packet dropping in computer networks. However, the conventional pacing is static in nature, meaning that constant pauses are introduced between packet transmissions to prevent bursty transmissions which can lead to delays at the receiver buffers. This paper therefore presents a congestion aware packet routing where the delay period is hinged on the prevailing network conditions. This dynamic pacing algorithm was designed and implemented in Spyder using Python programming language. It employed probe signals to gather network intelligence such as the applicable round trip times of the network. Thereafter, this network intelligence was employed to tailor the paces to these network conditions. The results obtained showed that this algorithm introduced longer paces when more packets are transmitted and shorter paces when few packets are transmitted. In so doing, this new algorithm gives enough time for large packets to be delivered and smaller paces when few packets are sent. The analysis was done in terms of bandwidth utilization efficiency, round trip times and congestion window size adjustments. The congestion window – time graphs and throughput – time graphs showed that the developed dynamic pacing algorithm adjusted quickly to network congestions hence ensuring that the network is efficiently utilized by averting delays

Index Terms

Cloud Computing

Congestion

Network Delays

Algorithm

TCP Pacing

Reference

  1. 1.
    Nouh, May Sayed A., et al. "Enhanced Route Discovery Mechanism of Ad-Hoc On Demand Distance Vector for MANET." International Journal of Computer Networks and Applications (IJCNA) 3.6: 129-138, 2016, DOI: 10.22247/ijcna/2016/48904
  2. 2.
    N. Tanida, M. Inaba, and K. Hiraki, “Adaptive auto-tuning of TCP pacing”, The University of Tokyo, Hongo Bunkyo Tokyo, Japan, pp. 1-14, 2015.
  3. 3.
    A. Aggarwal, S. Savage, and T. Anderson, “Understanding the Performance of TCP Pacing”, Department of Computer Science and Engineering University of Washington Seattle, pp. 1-9, 2015.
  4. 4.
    A.Nabil, T. Patrick, K. Robert, N. Vijay, M. Thomas, and B. Arkady, “ Secure and Resilient Cloud Computing for the Department of Defense”, Lincoln Laboratory Journal, Vol. 22, No. 1, pp. 123-135, 2016.
  5. 5.
    D. Sakhuja & A. Shukla, “Cloud Computing”, International Journal of Engineering Research & Technology (IJERT), Vol. 2, Issue 3, pp. 1-7, 2013.
  6. 6.
    B. Dennis, “Impact of Virtualization on Data Center Physical Infrastructure”, The Green grid, Vol. 27, pp. 1-10, 2010.
  7. 7.
    S. Karolj, D. Davor, A. Enis, S. Ivan, S. Zorislav, “Scalable Distributed Computing Hierarchy: Cloud, Fog and Dew Computing”, Open Journal of Cloud Computing, Vol. 2 (1), pp. 16–24, 2015.
  8. 8.
    M. Haghighat, S. Zonouz & M. Abdel-Mottaleb, “CloudID: Trustworthy Cloud-based and Cross-Enterprise Biometric Identification”, Expert Systems with Applications, Vol. 42, No. 21, pp. 7905–7916, 2015.
  9. 9.
    C. Lehmann, “ Hybrid multi-cloud architecture, and the vendors aiming to enable and manage it”, 451 Research, LLC, pp. 1-6, 2016.
  10. 10.
    M. Duke, R. Braden, W. Eddy, E. Blanton & A. Zimmermann, “A Roadmap for Transmission Control Protocol (TCP) Specification Documents”, Internet Engineering Task Force (IETF), pp. 1-57, 2015.
  11. 11.
    M. Ghobadi and Y. Ganjali, “TCP Pacing in Data Center Networks”, IEEE 21st Annual Symposium on High-Performance Interconnects, pp. 1-8, 2013.
  12. 12.
    K. Chaubey and P. Mistri, “An Encounter Based Routing in Delay Tolerant Network (DTN): A Hybrid Approach”, International Journal Of Innovative Research In Computer And Communication Engineering, Vol. 4, Issue 5, pp. 8657 - 8662 , 2016. DOI: 10.15680/IJIRCCE.2016. 0405085.
  13. 13.
    N. Dayanand and A. Vidhate, “Improved Routing Protocol for Delay Tolerant Network”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 6, Issue 4, pp. 688- 691, 2016.
  14. 14.
    S. Islam and M. Welzl, “Start Me Up: Determining and Sharing TCP’s Initial Congestion Window”, ACM, pp. 1-3, 2016. DOI: http://dx.doi.org/10.1145/2959424.2959440.
  15. 15.
    Rohini, G., and A. Srinivasan. "Dynamic Transition of Bandwidth and Power Saving Mechanism to Support Multimedia Streaming Using H. 264/SVC over the Wireless Networks." International Journal of Computer Networks and Applications 2.2 (2015): 57-63.
  16. 16.
    Merlyn, A. Anuba, and A. Anuja Merlyn. "Energy Efficient Routing (EER) For Reducing Congestion and Time Delay in Wireless Sensor Network." International Journal of Computer Networks and Applications 1.1 (2014): 1-10.
  17. 17.
    N. Hanford, B. Tierney and D. Ghosal, “Optimizing Data Transfer Nodes using Packet Pacing”, ACM, pp. 1-8, 2015, DOI: http://dx.doi.org/10.1145/2830318.2830322.
  18. 18.
    Y. Cai, Y. Sinan and T. Wolf, “Practical Packet Pacing in Small-Buffer Networks”, Department of Electrical and Computer Engineering University of Massachusetts, pp. 1-6, 2016.
  19. 19.
    F. Gratzer, “QUIC - Quick UDP Internet Connections”, Seminars FI / IITM SS 16, Network Architectures and Services, pp. 36-46, 2016, DOI: 10.2313/NET-2016-09-1_06.
  20. 20.
    W. Wang, L.Huang, C. Li, and X. Wang, “TCP-polite rate control based on cooperative measurement”, John Wiley & Sons, Ltd, Vol. 9, Issue 9 , pp. 899–909 ,2013, DOI: 10.1002/sec.901.
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