International Journal of Computer Network and Information Security (IJCNIS)
IJCNIS Vol. 10, No. 8, 8 Aug. 2018
Cover page and Table of Contents: PDF (size: 984KB)
Through the Diversity of Bandwidth-Related Metrics, Estimation Techniques and Tools: An Overview
Full Text (PDF, 984KB), PP.1-16
Views: 0 Downloads: 0
Author(s)
Fatih Abut
1,*
Index Terms
Capacity, Available Bandwidth, Throughput, Estimation Techniques, Active Probing, Quality of Service
Abstract
The knowledge of bandwidth in communication networks can be useful in various applications. Some popular examples are validation of service level agreements, traffic engineering and capacity planning support, detection of congested or underutilized links, optimization of network route selection, dynamic server selection for downloads and visualizing network topologies, to name just a few. Following these various motivations, a variety of bandwidth estimation techniques and tools have been proposed in the last decade and still, several new ones are currently being introduced. They all show a wide spectrum of different assumptions, characteristics, advantages and limitations. In this paper, the bandwidth estimation literature is reviewed, with focus on introducing four specific bandwidth-related metrics including capacity, available bandwidth, achievable throughput and bulk transfer capacity (BTC); describing the main characteristics, strengths and weaknesses of major bandwidth estimation techniques as well as classifying the respective tool implementations. Also, the fundamental challenges, practical issues and difficulties faced by designing and implementing bandwidth estimation techniques are addressed.
Cite This Paper
Fatih Abut, "Through the Diversity of Bandwidth-Related Metrics, Estimation Techniques and Tools: An Overview", International Journal of Computer Network and Information Security(IJCNIS), Vol.10, No.8, pp.1-16, 2018. DOI:10.5815/ijcnis.2018.08.01
Reference
[1]R. Prosad et al., “Bandwidth estimation: metrics, measurement techniques, and tools,” IEEE Netw., vol. 17, no. 6, pp. 27–35, 2003.
[2]C. D. Guerrero and M. A. Labrador, “On the applicability of available bandwidth estimation techniques and tools,” Comput. Commun., vol. 33, no. 1, pp. 11–22, 2010.
[3]A. S. Sairam, “Survey of Bandwidth Estimation
Techniques,” Wirel. Pers. Commun., pp. 1425–1476, 2015.
[4]K. Lai and M. Baker, “Nettimer: A tool for measuring bottleneck link bandwidth,” in Proceedings of the USENIX Symposium on Internet Technologies and Systems, 2001, vol. 134, pp. 1–12.
[5]A. B. Downey, “Using pathchar to estimate Internet link characteristics,” ACM SIGCOMM Comput. Commun. Rev., vol. 29, no. 4, pp. 241–250, 1999.
[6]X. Su, X. Yan, and C.-L. Tsai, “Linear regression,” Wiley Interdiscip. Rev. Comput. Stat., vol. 4, no. 3, pp. 275–294, 2012.
[7]R. S. Prasad, C. Dovrolis, and B. A. Mah, “The effect of layer-2 switches on pathchar-like tools,” Proc. Second ACM SIGCOMM Work. Internet Meas. - IMW ’02, no. 5, p. 321, 2002.
[8]V. Paxson, “End-to-end routing behavior in the internet,” IEEE/ACM Trans. Netw., vol. 5, no. 5, pp. 601–615, 1997.
[9]J. Strauss, D. Katabi, and F. Kaashoek, “A measurement study of available bandwidth estimation tools,” in Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC, 2003, pp. 39–44.
[10]A. O. Tang, J. Wang, S. Hegde, and S. H. Low, “Equilibrium and fairness of networks shared by TCP Reno and Vegas/FAST,” Telecommun. Syst., vol. 30, no. 4 SPEC. ISS., pp. 417–439, 2005.
[11]F. Abut, “Towards a Generic Classification and Evaluation Scheme for Bandwidth Measurement Tools,” Signals Telecommun. J., vol. 1, pp. 78–88, 2012.
[12]M. Jain and C. Dovrolis, “Pathload: a measurement tool for end-to-end available bandwidth,” in Proceedings of the Passive and Active Measurements (PAM) Workshop, 2002, pp. 1–12.
[13]K. Harfoush, A. Bestavros, and J. Byers, “Measuring capacity bandwidth of targeted path segments,” IEEE/ACM Trans. Netw., vol. 17, no. 1, pp. 80–92, 2009.
[14]C. Dovrolis, P. Ramanathan, and D. Moore, “What do packet dispersion techniques measure?,” Proc. - IEEE INFOCOM, vol. 2, pp. 905–914, 2001.
[15]S. Saroiu, P. Gummadi, and S. Gribble, “Sprobe: A fast technique for measuring bottleneck bandwidth in uncooperative environments,” IEEE INFOCOM, pp. 1–11, 2002.
[16]D. Antoniades, M. Athanatos, and A. Papadogiannakis, “Available bandwidth measurement as simple as running wget.”
[17]D. Croce, T. En-Najjary, G. Urvoy-Keller, and E. W. Biersack, “Non-cooperative available bandwidth estimation towards ADSL links,” in Proceedings - IEEE INFOCOM, 2008.
[18]R. Kapoor, L. Chen, and M. Gerla, “CapProbe?: A Simple and Accurate Capacity Estimation Technique,” in SIGCOMM ’04 Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications, 2004, pp. 67–68.
[19]C. L. T. Man, G. Hasegawa, and M. Murata, “An Inline measurement method for capacity of end-to-end network path,” in 3rd IEEE/IFIP Workshop on End-to-End Monitoring Techniques and Services, E2EMON, 2005, vol. 2005, pp. 56–70.
[20]A. B. Downey, “Clink,” 1999. [Online]. Available: http://rocky.xn--wellesley-3ma.edu/?downey/clink.
[21]M. Kazantzidis, D. Maggiorini, and M. Gerla, “Network independent available bandwidth sampling and measurement,” Lect. NOTES Comput. Sci., vol. 2601, pp. 117–130, 2003.
[22]S. Katti, D. Katabi, C. Blake, E. Kohler, and J. Strauss, “MultiQ: automated detection of multiple bottleneck capacities along a path,” IMC ’04 Proc. 4th ACM SIGCOMM Conf. Internet Meas., pp. 245–250, 2004.
[23]S. R. Kang and D. Loguinov, “IMR-Pathload: Robust available bandwidth estimation under end-host interrupt delay,” in Lecture Notes in Computer Science, 2008, vol. 4979 LNCS, pp. 172–181.
[24]C. L. T. Man, G. Hasegawa, and M. Murata, “ICIM: An Inline Network Measurement Mechanism for Highspeed Networks,” in 2006 4th IEEE/IFIP Workshop on End-to-End Monitoring Techniques and Services, 2006, pp. 66–73.
[25]G. Jin and B. L. Tierney, “System Capability Effects on Algorithms for Network Bandwidth Measurement,” Proc. 3rd ACM SIGCOMM Conf. Internet Meas., pp. 27–38, 2003.
[26]V. J. Ribeiro, R. H. Riedi, R. G. Baraniuk, and J. Navratil, “Spatio-temporal available bandwidth estimation for high-speed networks,” in ISMA 2003 Bandwidth Estimation Workshop, 2003, pp. 6–8.
[27]A. Tirumala, L. Cottrell, and T. Dunigan, “Measuring end-to-end bandwidth with Iperf using Web100,” Proc. Passiv. Act. Meas. Work., no. April, pp. 1–8, 2003.
[28]Y. Ozturk and M. Kulkarni, “DIChirp: Direct injection bandwidth estimation,” Int. J. Netw. Manag., vol. 18, no. 5, pp. 377–394, 2008.
[29]M. Neginhal, K. Harfoush, and H. Perros, “Measuring Bandwidth Signatures of Network Paths,” Network, pp. 1–12, 2007.
[30]M. Jain and C. Dovrolis, “End-to-end estimation of the available bandwidth variation range,” ACM SIGMETRICS Perform. Eval. Rev., vol. 33, no. 1, p. 265, 2005.
[31]C. Dovrolis, P. Ramanathan, and D. Moore, “Packet-dispersion techniques and a capacity-estimation methodology,” IEEE/ACM Trans. Netw., vol. 12, no. 6, pp. 963–977, 2004.
[32]L.-J. J. Chen, T. Sun, B.-C. C. Wang, M. Y. Y. Sanadidi, and M. Gerla, PBProbe: A capacity estimation tool for high speed networks, vol. 31, no. 17. 2008.
[33]L. Chen, T. Sun, G. Yang, M. Y. Sanadidi, and M. Gerla, “End-to-End Asymmetric Link Capacity Estimation,” in IFIP Networking, 2005, pp. 780–791.
[34]R. L. Carter and M. E. Crovella, “Dynamic server selection using bandwidth probing in wide-area networks,” IEEE InfoCom, vol. 97, no. April, p. 96-007, 1997.
[35]T. En-Najjary and G. Urvoy-Keller, “PPrate: A Passive Capacity Estimation Tool,” in 2006 4th IEEE/IFIP Workshop on End-to-End Monitoring Techniques and Services, 2006, pp. 82–89.
[36]B. A. Mah, “pchar: A Tool for Measuring Internet Path Characteristics,” 2001. [Online]. Available: http://www.employees.org/?bmah/Software/pchar/.
[37]J. Sommers, P. Barford, and W. Willinger, “Laboratory-based calibration of available bandwidth estimation tools,” Microprocess. Microsyst., vol. 31, no. 4 SPEC. ISS., pp. 222–235, 2007.
[38]E. Goldoni, G. Rossi, and A. Torelli, “Assolo, a New Method for Available Bandwidth Estimation,” 2009 Fourth Int. Conf. Internet Monit. Prot., pp. 130–136, 2009.
[39]M. ?adyga, R. H. Riedi, R. G. Baraniuk, J. Navratil, and L. Cottrell, “pathChirp: Efficient Available Bandwidth
Estimation for Network Paths,” in Passive and Active Measurement Workshop, 2003.
[40]N. Hu and P. Steenkiste, “Evaluation and characterization of available bandwidth probing techniques,” IEEE J. Sel. Areas Commun., vol. 21, no. 6, pp. 879–894, 2003.
[41]V. Ribeiro, M. Coates, R. Riedi, S. Sarvotham, B. Hendricks, and R. Baraniuk, “Multifractal cross-traffic estimation,” ITC Spec. Semin. IP Traffic Meas., pp. 1–15, 2000.
[42]“Netperf Homepage,” 2018. [Online]. Available: https://hewlettpackard.github.io/netperf/.
[43]M. Allman, “Measuring end-to-end bulk transfer capacity,” Proc. First ACM SIGCOMM Work. Internet Meas. Work. - IMW ’01, no. November, p. 139, 2001.
[44]M. Mathis and J. Mahdav, “iagnosing internet congestion with a transport layer performance tool,” in INET’96, 1996.