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Survey of Bandwidth Estimation Techniques in Communication Networks

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Abstract

Increased popularity and wealth-creation potential of conventional mobile phones, smart phones and tablet computers resulted in the unprecedented penetration of wired and wireless communications. Most of such real-time applications require video streaming that needs quality of service (QoS) provisioning in addition to good end-to-end transport performance in network infrastructure. Estimating the reliability of an end-to-end network path is critically important for such applications. Available bandwidth at a node is an important QoS characteristic of the path that is a minimum spare capacity of links constituting a network path. Researchers have proposed various techniques for estimating the bandwidth to increase the network throughput. In the past, bandwidth estimation (BE) techniques developed for wired networks are focused on point-to point dedicated links that are not directly usable in wireless networks. The reason is that these techniques are based on models which are no longer valid in wireless environment. This paper aims to provide a comprehensive survey of the BE techniques proposed till date by researchers in the literature for both wired and wireless networks. We have categorized the BE techniques into four main categories as active probing techniques, passive techniques, techniques only for wireless networks and other BE techniques. A brief outline of each technique is discussed which includes the problem statement, operation methodology, results and applications. Techniques in each category have been compared using various parameters such as accuracy, BE time and overhead.

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References

  1. Hanzo, L., Haas, H., Imre, S., O’Brien, D., Rupp, M., & Gyongyosi, L. (2012). Wireless myths, realities, and futures: From 3G/4G to optical and quantum wireless. Proceedings of the IEEE, 100(Special Centennial Issue), 1853–1888.

    Article  Google Scholar 

  2. Prasad, R. S., Murray, M., Dovrolis, C., & Claffy, K. C. (2003). Bandwidth estimation: Metrics. IEEE Network Measurement Techniques, and Tools, 17(6), 27–35.

    Article  Google Scholar 

  3. Johnsson, A., Melander, B., & Bjorkman, M. (2006). Bandwidth measurement in wireless networks challenges in ad hoc networking. In K. Al Agha, I. Guérin Lassous, & G. Pujolle (Eds.), International federation for information processing, Chap. 11 (Vol. 197, pp. 89–98). Boston: Springer.

  4. Patil, R., Damodaram, A., & Das, R. (2009). A cross layer approach for controlling jitter in MANET based on bandwidth estimation. In First Asian Himalayas international conference on internet (pp. 1–5).

  5. Croce, D., & Leonardi, E. (2011). Large-scale available bandwidth measurements. Interference in current techniques. IEEE Transactions on Network and Service Management, 8(4), 361–374.

    Article  Google Scholar 

  6. Arsan, T. (2012). Review of bandwidth estimation tools and application to bandwidth adaptive video streaming. In 9th international conference on high capacity optical networks and enabling technologies (pp. 152–156).

  7. Curtis, J., & Mcgregor, T. (2001). Review of bandwidth estimation techniques. In Computer science research students conference in New Zealand.

  8. Sarr, C., Chaudet, C., Chelius, G., & Lassous, I. G. (2008). Bandwidth estimation for IEEE 802.11-based ad hoc networks. IEEE Transaction on Mobile Computing, 7(10), 1228–1241.

    Article  Google Scholar 

  9. Li, M., Wu, Y.-L., & Chang, C.-R. (2013). Available bandwidth estimation for the network paths with multiple tight links and bursty traffic. Journal of Network and Computer Applications, 36(1), 353–367.

    Article  Google Scholar 

  10. Hu, N., & Steenkiste, P. (2003). Evaluation and characterization of available bandwidth probing techniques. IEEE Journal on Selected Areas in Communications, 21(6), 879–894.

    Article  Google Scholar 

  11. Tunali, T., & Anar, K. (2006). Adaptive available bandwidth estimation for internet video streaming. Signal Processing: Image Communication, 21(3), 217–234.

    Google Scholar 

  12. Ergin, M. A., Gruteser, M., Luo, L., Raychaudhuri, D., & Liu, H. (2008). Available bandwidth estimation and admission control for QoS routing in wireless mesh networks. Computer Communications, 31(7), 1301–1317.

    Article  Google Scholar 

  13. Selin, P., Hasegawa, K., & Obara, H. (2011). Available bandwidth measurement technique using impulsive packet probing for monitoring end-to-end service quality on the internet. In 17th Asia-Pacific conference on communications (pp. 518–523).

  14. Li, M., & Chang, C.-R. (2009). A two-way available bandwidth estimation scheme for multimedia streaming networks adopting scalable video coding. In IEEE Sarnoff symposium (pp. 1–6).

  15. Park, H. J., & Roh, B.-H. (2010). Accurate passive bandwidth estimation (APBE) in IEEE 802.11 wireless LANs. In Proceedings of the 5th international conference on ubiquitous information technologies and applications (pp. 1–4).

  16. Tursunova, S., Inoyatov, K., & Kim, Y.-T. (2010). Cognitive passive estimation of available bandwidth (cPEAB) in overlapped IEEE 802.11 WiFi WLANs. In IEEE network operations and management symposium (pp. 448–454).

  17. Hei, X., Bensaou, B., & Tsang, D. H. K. (2006). Model-based end-to-end available bandwidth inference using queueing analysis. Computer Networks, 50(12), 1916–1937.

    Article  MATH  Google Scholar 

  18. Barzuza, T., Ben Zedeff, S., Modai, O., Vainbrand, L., Wiener, Y., & Yellin E. (2010). TREND: A dynamic bandwidth estimation and adaptation algorithm for real-time video calling. In 18th international packet video workshop (pp. 126–133).

  19. Ali, R., & Zafar, F. (2011). Bandwidth estimation in mobile ad-hoc network (MANET). International Journal of Computer Science, 8(5), 331–337.

    Google Scholar 

  20. Zhao, H., Garcia-Palacios, E., Wei, J., & **, Y. (2009). Accurate available bandwidth estimation in IEEE 802.11-based ad hoc networks. Computer Communications, 32(6), 1050–1057.

    Article  Google Scholar 

  21. Hu, N., & Steenkiste, P. (2002). Estimating available bandwidth using packet pair probing (No. CMU-CS-02-166). CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE.

  22. Pasztor, A., & Veitch, D. (2002). Active probing using packet quartets. In Proceedings of the 2nd ACM SIGCOMM internet measurement workshop (pp. 293–305).

  23. Zhang, M., Luo, C., & Li, J. (2006). Estimating available bandwidth using multiple overloading streams. IEEE International Conference on Communications, 2, 495–502.

    Google Scholar 

  24. **ao, Y., Chen, S., Li, X., & Li, Y. (2007). A new available bandwidth measurement method based on self-loading periodic streams. In Wireless Communications, Networking and Mobile Computing, WiCom 2007, 21–25 Sept. 2007 (pp. 1904–1907). International Conference on IEEE.

  25. Ibrahim, M. F., & Taib, M. N. (2010). The deployment of end-to-end available bandwidth estimation mechanism in web-based application. In IEEE symposium on industrial electronics and applications (pp. 201–206).

  26. Yuan, Z., Venkataraman, H., & Muntean, G. M. (2009). iBE: A novel bandwidth estimation algorithm for multimedia services over IEEE 802.11 wireless networks. In Proceedings of the 12th IFIP/IEEE international conference on management of multimedia and mobile networks and services: Wired–wireless multimedia networks and services management (Vol. 5842, pp. 69–80).

  27. Lao, L., Dovrolis, C., & Sanadidi, M. Y. (2006). The probe gap model can underestimate the available bandwidth of multihop paths. ACM SIGCOMM Computer Communication Review, 36(5), 29–34.

    Article  Google Scholar 

  28. Obara, H., Koseki, S., & Selin, P. (2012). Packet train pair: A fast and efficient technique for measuring available bandwidth in the internet. In SICE annual conference (pp. 1833–1836).

  29. Cabello-Aparicio, A., Garcia, F. J., & Domingo-pascual, J. (2008). A novel available bandwidth estimation and tracing algorithm. In Network operations and management symposium workshops (pp. 87–94).

  30. Lin, H., Liu, M., Zhou, A., Liu, H., & Li, Z. C. (2010) A novel hybrid probing technique for end-to-end available bandwidth estimation. In IEEE 35th conference on local computer networks (pp. 400–407).

  31. Guerrero, C. D., & Labrador, M. A. (2010). On the applicability of available bandwidth estimation techniques and tools. Journal Computer Communications, 33(1), 11–22.

    Article  Google Scholar 

  32. Nam, S. Y., Kim, S., & Park, W. (2012). Analysis of minimal backlogging-based available bandwidth estimation mechanism. Journal Computer Communications, 35(4), 431–443.

    Article  Google Scholar 

  33. Nam, S. Y., Kim, S. J., Lee, S., & Kim, H. S. (2013). Estimation of the available bandwidth ratio of a remote link or path segments. Computer Networks, 57(1), 61–77.

    Article  Google Scholar 

  34. Hu, Z., Zhang, D., Zhu, A., Chen, Z., & Zhou, H. (2012). SLDRT: A measurement technique for available bandwidth on multi-hop path with bursty cross traffic. Computer Networks, 56(14), 3247–3260.

    Article  Google Scholar 

  35. Thouin, F., Coates, M., & Rabbat, M. (2011). Large scale probabilistic available bandwidth estimation. Computer Networks, 55(9), 2065–2078.

    Article  Google Scholar 

  36. Guerrero, C. D., & Labrador, M. A. (2010). Traceband: A fast, low overhead and accurate tool for available bandwidth estimation and monitoring. Computer Networks, 54(6), 977–990.

    Article  MATH  Google Scholar 

  37. Strauss, J., Katabi, D., & Kaashoek, F. (2003). A measurement study of available bandwidth estimation tools. In Proceedings of the 3rd ACM SIGCOMM conference on internet measurement (pp. 39–44).

  38. Jain, M., & Dovrolis, C. (2004). Ten fallacies and pitfalls on end-to-end available bandwidth estimation. In Proceedings of the 4th ACM SIGCOMM conference on internet measurement (pp. 272–277).

  39. Delphinanto, A., Koonen, T., Zhang, S., & den Hartog, F. (2010). Path capacity estimation in heterogeneous, best-effort, small-scale IP networks. In IEEE 35th conference on local computer networks (pp. 1076–1083).

  40. Turrubiartes, M., Torres, D., Angulo, M., & Munoz, D. (2005). Analysis of IP network path capacity estimation using a variable packet size method. In 15th international conference on electronics, communications and computers (pp. 177–182).

  41. Li, M., Claypool, M., & Kinicki, R. (2008). WBest: A bandwidth estimation tool for IEEE 802.11 wireless networks. In Proceedings of the 33rd IEEE conference on local computer networks, Montreal, Canada (pp. 374–381).

  42. Yuan, Z. (2012). MBE: Model-based available bandwidth estimation for IEEE 802.11 data communications. IEEE Transactions on Vehicular Technology, 61(5), 2158–2171.

    Article  Google Scholar 

  43. Yuan, Z., Venkataraman H., & Muntean, G. (2012). A novel bandwidth estimation algorithm for IEEE 802.11 TCP data transmissions. In IEEE wireless communications and networking conference workshops (pp. 377–382).

  44. Hoang, V. D., Shao, Z., & Fujise, M. (2006). A new solution to estimate the available bandwidth in MANETs. In IEEE 63rd vehicular technology conference (Vol. 2, pp. 653–657).

  45. Shin, P., & Chung, K. (2008). A cross-layer based rate control scheme for MPEG-4 video transmission by using efficient bandwidth estimation in IEEE 802.11e. In International conference on information networking (pp. 1–5).

  46. Zhu, Y., Dovrolis, C., & Ammar, M. (2006). Dynamic overlay routing based on available bandwidth estimation: A simulation study. Computer Networks, 50(6), 742–762.

    Article  Google Scholar 

  47. Downey, A. B. (1999). Using pathchar to estimate internet link characteristics. ACM SIGMETRICS Performance Evaluation Review, 27(1), 222–233.

    Article  Google Scholar 

  48. Downey, A. B. (1999). Clink: A tool for estimating internet llink characteristics. http://rocky.wellesley.edu/downey/clink/

  49. Downey, A. B. (1999). Using pathchar to estimate internet link characteristics. In ACM SIGCOMM Computer Communication Review (Vol. 29, No. 4, pp. 241–250). ACM.

  50. Mah, B. A. (2001). Pchar: A tool for measuring internet path characteristics. http://www.employees.org/bmah/Software/pchar/

  51. Lai, K., & Baker, M. (2000). Measuring link bandwidths using a deterministic model of packet delay. In Proceedings of the conference on applications, technologies, architectures, and protocols for computer communication (pp. 283–294).

  52. Jain, M. (2003). End-to-end available bandwidth: Measurement methodology, dynamics, and relation with TCP throughput. IEEE/ACM Transactions on Networking, 11(4), 537–549.

    Article  Google Scholar 

  53. Melander, B., Bjorkman, M., & Gunningberg, P. (2000). A new end-to-end probing and analysis method for estimating bandwidth bottlenecks. In IEEE global telecommunications conference (Vol. 1, pp. 415–420).

  54. Jain, M., & Dovrolis, C. (2002). Pathload: A measurement tool for end-to-end available bandwidth. In Proceedings of passive and active measurements workshop (pp. 14–25).

  55. Kiwior, D., Kingston, J., & Spratt, A. (2004). PathMon, a methodology for determining available bandwidth over an unknown network. In IEEE/Sarnoff symposium on advances in wired and wireless communication (pp. 27–30).

  56. Jain, M., & Dovrolis, C. (2005). End-to-end estimation of the available bandwidth variation range. In Proceeding of ACM SIGMETRICS international conference on measurement and modeling of computer systems (pp. 265–276).

  57. Riberio, J. V., Riedi, R., Baraniuk, R. G., Navratil, J., & Cottrell, L. (2003). pathChirp: Efficient available bandwidth estimation for network paths. In Proceeding of 4th passive active measurement workshop.

  58. Sommers, J., Barford, P., & Willinger, W. (2007). Laboratory-based calibration of available bandwidth estimation tools. Journal Microprocessors and Microsystems, 31(4), 222–235.

    Article  Google Scholar 

  59. Dey, B. K., Manjunath, D., & Chakraborty, S. (2011). Estimating network link characteristics using packet-pair dispersion: A discrete-time queueing theoretic analysis. Computer Networks, 55(5), 1052–1068.

    Article  MATH  Google Scholar 

  60. Park, K.-J., Lim, H., Hou, J. C., & Choi, C.-H. (2009). Feedback-assisted robust estimation of available bandwidth. Computer Networks, 53(7), 896–912.

    Article  MATH  Google Scholar 

  61. Bolot, J. C. (1993). End-to-end packet delay and loss behavior in the internet. In Proceeding ACM SIGCOMM symposium communications architectures protocols (pp. 289–298).

  62. Ribeiro, V., Coates, M., & Baraniuk, R. (2000). Multifractal cross-traffic estimation. In Proceedings of ITC specialist seminar IP traffic measurement, modeling, and management (pp. 15–22).

  63. Jain, M., & Dovrolis, C. (2003). End-to-end available bandwidth: Measurement methodology, dynamics, and relation with TCP throughput. IEEE/ACM Transactions on Networking, 11(4), 537–549.

    Article  Google Scholar 

  64. Carter, R., & Crovella, M. (1996). Measuring bottleneck link speed in packet-switched networks. Journal on Performance Evaluation, 27–28, 297–318.

    Article  Google Scholar 

  65. Lai, K., & Baker, M. (2000). Measuring link bandwidths using a deterministic model of packet delay. ACM SIGCOMM Computer Communication Review, 30(4), 283–294.

    Article  Google Scholar 

  66. Paxson, V. (1999). End-to-end internet packet dynamics. IEEE/ACM Transactions on Networking, 7(3), 277–292.

    Article  Google Scholar 

  67. Mathis, M., & Mahdavi, J. (1996). Diagnosing internet congestion with a transport layer performance tool. In Proceedings of INET at Montreal, Quebec, Canada.

  68. Zhou, H. (2011). Measuring available bandwidth for smart cyber-physical applications. Tsinghua Science and Technology, 16(6), 601–610.

    Article  Google Scholar 

  69. Lai, K., & Baker, M. (2001). Nettimer: A tool for measuring bottleneck link bandwidth. In Proceedings of USENIX symposium internet technologies and systems (Vol. 3, pp. 123–134).

  70. Allman, M. (2001). Measuring end-to-end bulk transfer capacity. In ACM SIGCOMM internet measurement workshop.

  71. Angrisani, L., DAntonio, S., Esposito, M., & Vadursi, M. (2006). Techniques for available bandwidth measurement in IP networks: A performance comparison. Computer Networks, 50(3), 332–349.

    Article  Google Scholar 

  72. Vuletic, P. V., & Protic, J. (2011). Self-similar cross-traffic analysis as a foundation for choosing among active available bandwidth measurement strategies. Computer Communications, 34(10), 1145–1158.

    Article  Google Scholar 

  73. Aceto, G., Botta, A., Pescape, A., & D’Arienzo, M. (2012). Unified architecture for network measurement: The case of available bandwidth. Journal of Network and Computer Applications, 35(5), 1402–1414.

    Article  Google Scholar 

  74. Ekelin, S., Nilsson, M., Hartikainen, E., Johnsson, A., Mngs, J.-E., Melander, B., et al. (2006). Real-time measurement of end-to-end available bandwidth using Kalman filtering. In Proceedings of the 10th IEEE/IFIP network operations and management symposium.

  75. Bergfeldt, E., Ekelin, S., & Karlsson, J. M. (2009). Real-time available-bandwidth estimation using filtering and change detection. Computer Networks, 53(15), 2617–2645.

    Article  MATH  Google Scholar 

  76. Sedighizad, M., Seyfe, B., & Navaie, K. (2012). MR-BART: Multi-rate available bandwidth estimation in real-time. Journal of Network and Computer Applications, 35(2), 731–742.

    Article  Google Scholar 

  77. Calafate, C. T., Manzoni, P., & Malumbres, M. P. (2005). Supporting soft real-time services in MANETs using distributed admission control and IEEE 802.11e technology. In 10th IEEE symposium on computers and communications (pp. 217–222).

  78. Hoang, V. D., Shao, Z., & Fujise, M. (2006). Efficient load balancing in MANETS to improve network performance. In 6th international conference on ITS telecommunications proceedings (pp. 753–756).

  79. Alzate, M. A., Pagn, J.-C., Pea, N. M., & Labrador, M. A. (2008). End-to-end bandwidth and available bandwidth estimation in multi-hop IEEE 802.11b ad hoc networks. In 42nd annual conference on information sciences and systems (pp. 659–664).

  80. Johnsson, A., Melander, B., & Bjorkman, M. (2004). DietTOPP: A first implementation and evaluation of a simplified bandwidth measurement method. In Proceedings of Computer Network Workshop.

  81. Sun, T., Yang, G., Chen, L., Sanadidi, M. Y., & Geria, M. (2005). A measurement study of path capacity in 802.11b based wireless networks. In Proceedings international workshop on wireless traffic measurement model (pp. 31–37).

  82. Lakshminarayanan, K., Padmanabhan, V. N., & Padhye, J. (2004). Bandwidth estimation in broadband access networks. In Proceeding ACM SIGCOMM conference on internet measurement (pp. 314–321).

  83. Oetiker, T., & Rand, D. (1998). Multi router traffic grapher. In Proceedings of the 12th USENIX conference on system administration (pp. 141–148).

  84. Brakmo, L. S., & Peterson, L. L. (1995). TCP Vegas: End-to-end congestion avoidance on a global internet. IEEE Journal on Selected Areas in Communications, 13(8), 1465–1480.

    Article  Google Scholar 

  85. Casetti, C., Gerla, M., Mascolo, S., Sanadidi, M. Y., & Wang, R. (2002). TCP Westwood: Congestion control with faster recovery. Journal of Wireless Networks, 8(5), 467–479.

    Article  MATH  Google Scholar 

  86. Ahuja, K., Khanna, R., & Singh, B. (2011). Real-time available-bandwidth estimation (ABE) algorithm based selection in heterogeneous network for WiMAX and 3G. In 5th international conference on next generation mobile applications, services and technologies (pp. 169–174).

  87. de Renesse, R., Ghassemian, M., Friderikos, V., & Aghvami, A. H. (2004). QoS enabled routing in mobile ad hoc networks. In Fifth IEE international conference on 3G mobile communication technologies (pp. 678–682).

  88. Chaudet, C., & Lassous, I. G. (2002). BRuIT: Bandwidth reservation under interferences influence. In Proceedings of the European wireless.

  89. Yang, Y., & Kravets, R. (2005). Contention aware admission control for ad hoc networks. IEEE Transaction on Mobile Computing, 4(4), 363–377.

    Article  Google Scholar 

  90. de Renesse, R., Ghassemian, M., Friderikos, V., & Aghvami, A. H. (2005). Adaptive admission control for ad hoc and sensor networks providing quality of service. Technical Report, King College London.

  91. Sabojil, S. V., & Akki, C. B. (2011). Agent based bandwidth estimation in heterogeneous wireless networks. In 3rd international conference on advances in recent technologies in communication and computing (pp. 256–258).

  92. Yan, Z., Dapeng, W., Bin, W., Muqing, W., & Chunxiu, X. (2008). A novel call admission control routing mechanism for 802.11e based multi-hop MANET. In 4th international conference on wireless communications, networking and mobile computing (pp. 1–4).

  93. Peng, Y., & Yan, Z. (2012). Available bandwidth estimating method in IEEE802.11e based mobile ad hoc network. In 9th international conference on fuzzy systems and knowledge discovery (pp. 2138–2142).

  94. Chen, L., & Heinzelman, W. B. (2005). QoS-aware routing based on bandwidth estimation for mobile ad hoc networks. IEEE Journal on Selected Areas in Communications, 23(3), 561–572.

    Article  Google Scholar 

  95. Nyambo, B. M., Mugumba, J., & Janssens, G. K. (2007). A dual bandwidth estimation method for wireless mobile ad hoc networks. AFRICON, 2007, 1–6.

    Google Scholar 

  96. **ng, X., Dang, J., Mishra, S., & Liu, X. (2011). A highly scalable bandwidth estimation of commercial hotspot access points. In Proceedings IEEE INFOCOM (pp. 1143–1151).

  97. Shah, S. H., Chen, K., & Nahrstedt, K. (2003). Available bandwidth estimation in IEEE 802.11-based wireless networks. In Proceedings of 1st ISMA/CAIDA workshop on bandwidth estimation.

  98. Dapeng, W., Zhen, Y., Bing, S., Chunxiu, X., & Muqing, W. (2008). Improving accuracy of bandwidth estimation based on retransmission predicting in MANET. In 4th international conference on wireless communications, networking and mobile computing (pp. 1–4).

  99. **ng, X., Jiang, Y., & Mishra, S. (2011). Understanding characteristics of available bandwidth in wireless environment. Procedia Computer Science, 5, 248–254.

    Article  Google Scholar 

  100. Alzate, M. A., Pea, N. M., & Labrador, M. A. (2008). Capacity, bandwidth and available bandwidth concepts for wireless ad hoc networks. In IEEE military communications conference (pp. 1–7).

  101. Ge, Z., & Li, T. (2008). QoS routing based on service differentiation supported bandwidth estimation for MANET. In 4th international conference on wireless communications, networking and mobile computing (pp. 1–5).

  102. Capone, A., Fratta, L., & Martignon, F. (2004). Bandwidth estimation schemes for TCP over wireless networks. IEEE Transactions on Mobile Computing, 3(2), 129–143.

    Article  Google Scholar 

  103. Rong, L., Ruimin, L., & Zhigang, C. (2009). Cross-layer designed effective bandwidth estimation for broadband multimedia satellite networks with adaptive forward error control. In International conference on wireless communications and signal processing (pp. 1–5).

  104. Lee, H. K., Hall, V., Yum, K. H., Kim, K. I., & Kim, E. J. (2006). Bandwidth estimation in wireless LANs for multimedia streaming services. In IEEE international conference on multimedia and expo (pp. 1181–1184).

  105. Zhao, H., Garcia-Palacios, E., Wang, S., Wei, J., & Ma, D. (2013). Evaluating the impact of network density, hidden nodes and capture effect for throughput guarantee in multi-hop wireless networks. Ad Hoc Networks, 11(1), 54–69.

    Article  Google Scholar 

  106. Liebeherr, J., Fidler, M., & Valaee, S. (2010). A system-theoretic approach to bandwidth estimation. IEEE/ACM Transactions on Networking, 18(4), 1040–1053.

    Article  Google Scholar 

  107. Chobanyan, A., Mutka, M., Mandrekar, V., & **, N. (2008). End-to-end available bandwidth as a random autocorrelated QoS-relevant time-series. Computer Networks, 52(6), 1220–1237.

    Article  MATH  Google Scholar 

  108. Vieira, F. H. T., & Lee, L. L. (2009). Adaptive wavelet-based multifractal model applied to the effective bandwidth estimation of network traffic flows. IET Communications, 3(6), 906–919.

    Article  Google Scholar 

  109. Man, C. L. T., Hasegawa, G., & Murata, M. (2006). ImTCP: TCP with an inline measurement mechanism for available bandwidth. Computer Communications, 29(10), 1614–1626.

    Article  Google Scholar 

  110. Zhou, W., Ramakrishnan, S., Sarkar, D., & Sarkar, U. K. (2003). Bandwidth estimation for multiplexed videos using MMG-based single video traffic model. In IEEE global telecommunications conference (Vol. 6, pp. 3564–3568).

  111. Camarda, P., & Striccoli, D. (2004). Queueing networks approach for bandwidth estimation of smoothed VBR video streams. Journal Performance Evaluation, 57(1), 1–18.

    Article  Google Scholar 

  112. Son, S.-C., Lee, B.-T., Gwak, Y.-W., & Nam, J.-S. (2010). Fast required bandwidth estimation technique for network adaptive streaming. IEEE Transactions on Consumer Electronics, 56(3), 1442–1449.

    Article  Google Scholar 

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Acknowledgments

The authors wish to thank Visvesvaraya Technological University (VTU), Karnataka, INDIA, for funding the part of the project under VTU Research Scheme (Grant No. VTU/Aca./2011-12/A-9/753, Dated: 5 May 2012.

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Chaudhari, S.S., Biradar, R.C. Survey of Bandwidth Estimation Techniques in Communication Networks. Wireless Pers Commun 83, 1425–1476 (2015). https://doi.org/10.1007/s11277-015-2459-2

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