Overhead in available bandwidth estimation tools: Evaluation and analysis

Current Available Bandwidth Estimation Tools (ABET) insert into the network probing packets to perform a single estimation. The utilization of these packets makes ABET intrusive and prone to errors since they consume part of the available bandwidth they are measuring. This paper presents a comparati...

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Autores:
Salcedo Morillo, Dixon David
Guerrero, Julián
Guerrero, Cesar D
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
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oai:repositorio.cuc.edu.co:11323/2240
Acceso en línea:
https://hdl.handle.net/11323/2240
https://repositorio.cuc.edu.co/
Palabra clave:
Available bandwidth estimation
Overhead
Internet measurement tools
Network monitoring
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id RCUC2_651ae2bf40426a921321845b840ddfb2
oai_identifier_str oai:repositorio.cuc.edu.co:11323/2240
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Overhead in available bandwidth estimation tools: Evaluation and analysis
title Overhead in available bandwidth estimation tools: Evaluation and analysis
spellingShingle Overhead in available bandwidth estimation tools: Evaluation and analysis
Available bandwidth estimation
Overhead
Internet measurement tools
Network monitoring
title_short Overhead in available bandwidth estimation tools: Evaluation and analysis
title_full Overhead in available bandwidth estimation tools: Evaluation and analysis
title_fullStr Overhead in available bandwidth estimation tools: Evaluation and analysis
title_full_unstemmed Overhead in available bandwidth estimation tools: Evaluation and analysis
title_sort Overhead in available bandwidth estimation tools: Evaluation and analysis
dc.creator.fl_str_mv Salcedo Morillo, Dixon David
Guerrero, Julián
Guerrero, Cesar D
dc.contributor.author.spa.fl_str_mv Salcedo Morillo, Dixon David
Guerrero, Julián
Guerrero, Cesar D
dc.subject.spa.fl_str_mv Available bandwidth estimation
Overhead
Internet measurement tools
Network monitoring
topic Available bandwidth estimation
Overhead
Internet measurement tools
Network monitoring
description Current Available Bandwidth Estimation Tools (ABET) insert into the network probing packets to perform a single estimation. The utilization of these packets makes ABET intrusive and prone to errors since they consume part of the available bandwidth they are measuring. This paper presents a comparative of Overhead Estimation Tools (OET) analysis of representative ABET: Abing, Diettopp, Pathload, PathChirp, Traceband, IGI, PTR, Assolo, and Wbest. By using Internet traffic, the study shows that the insertion of probing packets is a factor that affects two metrics associated to the estimation. First, it is shown that the accuracy is affected proportionally to the amount of probing traffic. Secondly, the Estimation Time (ET) is increased in high congested end-to-end links when auto-induced congestion tools are used
publishDate 2017
dc.date.issued.none.fl_str_mv 2017
dc.date.accessioned.none.fl_str_mv 2019-01-25T14:50:53Z
dc.date.available.none.fl_str_mv 2019-01-25T14:50:53Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/ART
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
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dc.identifier.issn.spa.fl_str_mv 20760930
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/2240
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 20760930
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/2240
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv 1] E. Zhang, “Bandwidth Estimation for Virtual Networks,” PhD thesis, University of Nebraska Lincoln, 2015. [2] S. Baghermousavi, H. Rashidi, and H. Haghighi, “An approach to reduce qos monitoring overhead in ESB,” in e-Commerce in Developing Countries: With Focus on e-Trust (ECDC), 2014 8th International Conference on, pp. 1–5, 2014. [3] S. Lee, K. Levanti, and H. Kim, “Network monitoring: Present and future,” Computer Networks, Vol. 65, pp. 84 – 89, 2014. [4] A. Botta, A. Davy, B. Meskill, and G. Aceto, “Active techniques for available bandwidth estimation: Comparison and application,” in Data Traffic Monitoring and Analysis (E. Biersack, C. Callegari, and M. Matijasevic, eds.), Vol. 7754 of Lecture Notes in Computer Science, pp. 28–43, Springer Berlin Heidelberg, 2013. [5] M. Li, Y. Wu, and C. Chang, “Available bandwidth estimation for the network paths with multiple tight links and bursty traffic,” Journal of Network and Computer Applications, Vol. 36, no. 1, pp. 353 – 367, 2013. [6] S. Nam, S. Kim, S. Lee, and H. Kim, “Estimation of the available bandwidth ratio of a remote link or path segments,” Computer Networks, Vol. 57, no. 1, pp. 61–77, 2013. [7] C. Guerrero and M. Labrador, “A hidden markov model approach to available bandwidth estimation and monitoring,” in Internet Network Management Workshop, 2008. INM 2008. IEEE, pp. 1–6, 2008. [8] N. Jeyanthi, N. C. Iyengar, P. Kumar, and A. Kannammal, “An enhanced entropy approach to detect and prevent DDoS in cloud environment,” International Journal of Communication Networks and Information Security, Vol. 5, no. 2, pp. 110, 2013. [9] A. K. Paul, A. Tachibana, and T. Hasegawa, “Next: New enhanced available bandwidth measurement technique, algorithm and evaluation,” in 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC), pp. 443–447, IEEE, 2014. [10] K. Chan, “Testing and Measurement: Techniques and Applications,” Proceedings of the 2015 International Conference on Testing and Measurement Techniques (TMTA 2015), pp. 16-17, January 2015, Phuket Island, Thailand. CRC Press, 2015. [11] J. Kim and Y. Lee, “An end-to-end measurement and monitoring technique for the bottleneck link capacity and its available bandwidth,” Computer Networks, Vol. 58, pp. 158 – 179, 2014. [12] C. Guerrero and D. Morillo, “On the reduction of the available bandwidth estimation error through clustering with k-means,” in 2012 IEEE Latin-America Conference on Communications, pp. 1–5, 2012. [13] A. Ali, F. Michaut, and F. Lepage, “End-to-end available bandwidth measurement tools: A comparative evaluation of performances,” CoRR (Computing Research Repository), Vol. abs/0706.4004, p. 13, 2007. [14] G. Urvoy-Keller, T. En-Najjary, and A. Sorniotti, “Operational com parison of available bandwidth estimation tools,” SIGCOMM Comput. Commun. Rev. Vol. 38, pp. 39–42, 2008. [15] S. Nam, S. Kim, and D. Sung, “Estimation of available bandwidth for a queueing system,” Applied Mathematical Modelling, Vol. 33, no. 8, pp. 3299 – 3308, 2009. [16] C. Man, G. Hasegawa, and M. Murata, “A simultaneous inline measurement mechanism for capacity and available bandwidth of end to end network path,” IEICE TRANSACTIONS on Communications, Vol. E89-B No.9, pp. 2469 – 2479, 2006. [17] V. Ribeiro, R. Riedi, R. Baraniuk, J. Navratil, and L. Cottrell, “Pathchirp: Efficient available bandwidth estimation for network paths,” DARPA/AFRL, NSF, Texas Instruments, SLAC - Stanford, 2003. [18] R. Kapoor, C. Lao, L. Chen, Gerla, and Y. Sanadidi, “Capprobe: A simple and accurate capacity estimation technique,” in ACM SIGCOMM Computer Communication Review, Vol. 34, pp. 67–78, 2004. [19] C. Guerrero and M. Labrador, “Experimental and analytical evaluation of available bandwidth estimation tools,” in Local Computer Networks, Proceedings 2006 31st IEEE Conference on, pp. 710–717, 2006. [20] A. Shriram, M. Murray, Y. Hyun, N. Brownlee, A. Broido, M. Fomenkov, and K. Claffy, “Comparison of public end-to-end bandwidth estimation tools on high speed links,” in Proceedings of the 6th International Conference on Passive and Active Network Measurement, PAM’05, (Berlin, Heidelberg), pp. 306–320, 2005. [21] M. Jain and C. Dovrolis, “Ten fallacies and pitfalls on end-toend available bandwidth estimation,” in Proceedings of the 4th ACM SIGCOMM Conference on Internet Measurement, IMC ’04, (New York, NY, USA), pp. 272–277, 2004. [22] U. Nguyen, D. Tran, and G. Nguyen, “A taxonomy of applying filter techniques to improve the available bandwidth estimations,” in Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC ’14, (New York, NY, USA), pp. 18:1–18:8, 2014. [23] H. Zhou, Y. Wang, X. Wang, and X. Huai, “Difficulties in estimating available bandwidth,” in Communications, 2006. ICC ’06. IEEE International Conference on, Vol. 2, pp. 704– 709, June 2006. [24] F. Michaut and F. Lepage, “Application-oriented network metrology: Metrics and active measurement tools,” Communications Surveys Tutorials, IEEE, Vol. 7, pp. 2–24, Second 2005. [25] R. K. Mok, W. Li, and R. K. Chang, “Improving the packet send-time accuracy in embedded devices,” in International Conference on Passive and Active Network Measurement, pp. 332–344, 2015.[26] J. Kiciński and K. Nowicki, “Using statistical methods to estimate the worst case response time of network software running on indeterministic hardware platforms,” Journal of Computer Science and Software Application, Vol. 1, pp. 42- 62, 2014. [27] C. Man, G. Hasegawa, and M. Murata, “Inline bandwidth measurement techniques for gigabit networks,” Int. Journal. Internet Protoc. Technol. IJIPTCao LE THANH MAN, Vol. 3, pp. 81–94, 2008. [28] G. Aceto, A. Botta, A. Pescapè, and M. D’Arienzo, “Unified architecture for network measurement: The case of available bandwidth,” Journal of Network and Computer Applications, Vol. 35, no. 5, pp. 1402– 1414, 2012. [29] J. Strauss, D. Katabi, and F. Kaashoek, “A measurement study of available bandwidth estimation tools,” in Proceedings of the 3rd ACM SIGCOMM Conference on Internet Measurement, IMC ’03, (New York, NY, USA), pp. 39–44, 2003. [30] M. Jain and C. Dovrolis, “Pathload: A measurement tool for end-to-end available bandwidth,” in In Proceedings of Passive and Active Measurements (PAM) Workshop, pp. 14–25, 2002. [31] N. Hu and P. Steenkiste, “Evaluation and characterization of available bandwidth probing techniques,” Selected Areas in Communications, IEEE Journal, Vol. 21, pp. 879–894, 2003. [32] S. Abolfazli, Z. Sanaei, S. Wong, A. Tabassi, and S. Rosen, “Throughput measurement in 4G wireless data networks: Performance evaluation and validation,” in Computer Applications & Industrial Electronics (ISCAIE), 2015 IEEE Symposium on, pp. 27–32, 2015. [33] B. Cavusoglu and E. Oral, “Estimation of available bandwidth share by tracking unknown cross-traffic with adaptive extended kalman filter,” Computer Communications, Vol. 47, no. 58, pp. 34–50, 2014. [34] K. Dichev, F. Reid, and A. Lastovetsky, “Efficient and reliable network tomography in heterogeneous networks using bittorrent broadcasts and clustering algorithms,” in Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC ’12, (Los Alamitos, CA, USA), pp. 36:1–36:11, 2012. [35] L. Daniel and M. Kojo, “Enhancing TCP with cross-layer notifications and capacity estimation in heterogeneous access networks,” in Local Computer Networks (LCN), 2012 IEEE 37th Conference on, pp. 392–400, 2012. [36] P. Vuletić and J. Protić, “Self-similar cross-traffic analysis as a foundation for choosing among active available bandwidth measurement strategies,” Computer Communications, Vol. 34, no. 10, pp. 1145 – 1158, 2011. [37] F. Thouin, M. Coates, and M. Rabbat, “Large scale probabilistic available bandwidth estimation,” Computer Networks, Vol. 55, no. 9, pp. 2065 – 2078, 2011. [38] P. Dely, A. Kassler, L. Chow, N. Bambos, N. Bayer, H. Einsiedler, and C. Peylo, “BEST-AP: Non-intrusive estimation of available bandwidth and its application for dynamic access point selection,” Computer Communications, Vol. 39, pp. 78 – 91, 2014. [39] Z. Yuan, H. Venkataraman, and G. Muntean, “MBE: Modelbased available bandwidth estimation for IEEE 802.11 data communications,” Vehicular Technology, IEEE Transactions on, Vol. 61, pp. 2158–2171, 2011. [40] Z. Yuan, H. Venkataraman, and G. Muntean, “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: WiredWireless Multimedia Networks and Services Management, MMNS 2009, (Berlin, Heidelberg), pp. 69–80, 2009. [41] M. Alzate, J. Pagan, N. Pena, and M. Labrador, “End-to-end bandwidth and available bandwidth estimation in multi-hop IEEE 802.11b ad hoc networks,” in Information Sciences and Systems, 2008. CISS 2008. 42nd Annual Conference on, pp. 659–664, 2008. [42] M. Ergin, M. Gruteser, L. Luo, D. Raychaudhuri, and H. Liu, “Available bandwidth estimation and admission control for QoS routing in wireless mesh networks,” Computer Communications - Special Issue: Resource Management and routing in Wireless Mesh Networks, Vol. 31, no. 7, pp. 1301– 1317, 2008. [43] K. Lakshminarayanan, V. Padmanabhan, and J. Padhye, “Bandwidth estimation in broadband access networks,” in Proceedings of the 4th ACM SIGCOMM Conference on Internet Measurement, IMC ’04, (New York, NY, USA), pp. 314–321, 2004. [44] J. Navratil and R. Cottrell, “ABwE: A practical approach to available bandwidth estimation,” in In Passive and Active Measurement (PAM) Workshop 2003 Proceedings, La Jolla, 2003. [45] E. Goldoni, G. Rossi, and A. Torelli, “Assolo, a new method for available bandwidth estimation,” in Internet Monitoring and Protection, 2009. ICIMP’09. Fourth International Conference on, pp. 130–136, 2009. [46] A. Johnsson, B. Melander, and M. Bjӧrkman, “Diettopp: A first implementation and evaluation of a simplified bandwidth measurement method,” in Second Swedish National Computer Networking Workshop, Vol. 5, 2004. [47] C. Guerrero and M. Labrador, “Traceband: A fast, low overhead and accurate tool for available bandwidth estimation and monitoring,” Computer Networks, Vol. 54, no. 6, pp. 977 – 990, 2010. [48] M. Li, M. Claypool, and R. Kinicki, “Wbest: A bandwidth estimation tool for IEEE 802.11 wireless networks,” in 2008 33rd IEEE Conference on Local Computer Networks (LCN), pp. 374–381, IEEE, 2008. [49] A. Turner and M. Bing, “Tcpreplay: Pcap editing and replay tools for*nix,” online], http://tcpreplay. sourceforge. net, 2005. [50] V. Jacobson, “Congestion avoidance and control,” in ACM SIGCOMM computer communication review, Vol. 18, pp. 314–329, 1988. [51] V. Jacobson, “Pathchar: a tool to infer characteristics of internet paths,” in Mathematical Sciences Research InstituteMSRI of National Science Foundation Division of Mathematical Sciences-NSF, 1997. [52] V. Paxson, “End-to-end internet packet dynamics,” SIGCOMM Comput. Common. Rev, Vol. 27, pp. 139–152, 1997. [53] V. Paxson, “Fast, approximate synthesis of fractional gaussian noise for generating self-similar network traffic,” ACM SIGCOMM Computer Communication Review, Vol. 27, no. 5, pp. 5–18, 1997. [54] D. Villa and C. Castellanos, “Study of available bandwidth estimation techniques to be applied in packet-switched mobile networks,”. Aalborg University. Department of Communication Technology, 2006. [55] R. Prasad, C. Dovrolis, M. Murray, and K. Claffy, “Bandwidth estimation: Metrics, measurement techniques, and tools,” Network, IEEE, Vol. 17, pp. 27–35, 2003. [56] M. Jain and C. Dovrolis, “End-to-end available bandwidth: Measurement methodology, dynamics, and relation with TCP throughput,” Networking, IEEE/ACM Transactions on, Vol. 11, pp. 537–549, 2003. [57] A. Downey, “Using pathchar to estimate internet link characteristics,” SIGCOMM Comput. Commun. Rev, Vol. 29, pp. 241–250, 1999. [58] A. Botta, A. Pescapè, and G. Ventre, “On the performance of bandwidth estimation tools,” in Systems Communications, 2005. Proceedings, pp. 287–292, 2005. [59] C. Guerrero and M. Labrador, “On the applicability of available bandwidth estimation techniques and tools,” Computer Communications, Vol. 33, no. 1, pp. 11 – 22, 2010. [60] E. Goldoni and M. Schivi, “End-to-end available bandwidth estimation tools, an experimental comparison,” Traffic Monitoring and Analysis, Vol. 6003 of Lecture Notes in Computer Science, pp. 171–182, 2010. [61] Z. Xiaodan, “The application-orientated measurement performance evaluation of the end-to-end available bandwidth,” in Advanced Research and Technology in Industry Applications (WARTIA), 2014 IEEE Workshop on, pp. 573–577, 2014. [62] A. K. Paul, A. Tachibana, and T. Hasegawa, “Next-fit: Available bandwidth measurement over 4G/LTE networks–a curve-fitting approach,” in 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA), pp. 25–32, 2016. [63] P. Low and M. Alias, “Enhanced bandwidth estimation design based on probe-rate model for multimedia network,” in Telecommunication Technologies (ISTT), 2014 IEEE 2nd International Symposium on, pp. 198–203, 2014. [64] H. Sadeghian, A. Farahani, and M. Abbaspour, “Overheadcontrolled contention-based routing for vanets,” International Journal of Communication Networks and Information Security, Vol. 6, no. 2, p. 118, 2014. [65] J. Akpojaro, P. Aigbe, and D. Oyemade, “A cost-based approach for analysis the overheads of multicast protocols in non-strictly hierarchical networks,” International Journal of Communication Networks and Information Security, Vol. 3, no. 1, p. 67, 2011. [66] G. Jin and B. L. Tierney, “System capability effects on algorithms for network bandwidth measurement,” in Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement, pp. 27–38, 2003. [67] M. Zec, M. Mikuc, and M. Zagar, “Estimating the impact of interrupt coalescing delays on steady state TCP throughput,” in International Conference on Software, Telecommunications and Computer Networks (SoftCOM), 2002. [68] Z. Hu, D. Zhang, A. Zhu, Z. Chen, and H. Zhou, “SLDRT: A measurement technique for available bandwidth on multi-hop path with bursty cross traffic,” Computer Networks, Vol. 56, no. 14, pp. 3247 – 3260, 2012. [69] D. Croce, M. Mellia, and E. Leonardi, “The quest for bandwidth estimation techniques for large-scale distributed systems,” SIGMETRICS Perform. Eval. Rev, Vol. 37, pp. 20–25, 2010. [70] C. Man, G. Hasegawa, and M. Murata, “IMTCP: TCP with an inline measurement mechanism for available bandwidth,” Computer Communications, Vol. 29, no. 10, pp. 1614–1626, 2006. [71] C. Man, G. Hasegawa, and M. Murata, “Available bandwidth measurement via TCP connection,” in In Proceedings of IFIP/IEEE MMNS 2004 (E2EMON Workshop, pp. 38–44, 2004. [72] M. Zangrilli and B. Lowekamp, “Comparing passive network monitoring of grid application traffic with active probes,” in Proceedings of the 4th International Workshop on Grid Computing, GRID ’03-IEEE Computer Society, (Washington, DC, USA), pp. 84-91, 2003.
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spelling Salcedo Morillo, Dixon DavidGuerrero, JuliánGuerrero, Cesar D2019-01-25T14:50:53Z2019-01-25T14:50:53Z201720760930https://hdl.handle.net/11323/2240Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Current Available Bandwidth Estimation Tools (ABET) insert into the network probing packets to perform a single estimation. The utilization of these packets makes ABET intrusive and prone to errors since they consume part of the available bandwidth they are measuring. This paper presents a comparative of Overhead Estimation Tools (OET) analysis of representative ABET: Abing, Diettopp, Pathload, PathChirp, Traceband, IGI, PTR, Assolo, and Wbest. By using Internet traffic, the study shows that the insertion of probing packets is a factor that affects two metrics associated to the estimation. First, it is shown that the accuracy is affected proportionally to the amount of probing traffic. Secondly, the Estimation Time (ET) is increased in high congested end-to-end links when auto-induced congestion tools are usedSalcedo Morillo, Dixon David-0000-0002-3762-8462-600Guerrero, Julián-8bb47eee-941c-4f05-b3a4-e1c7b079bb3e-0Guerrero, Cesar D-0485700f-f924-41ee-be6f-8169cbfe03da-0engInternational Journal of Communication Networks and Information SecurityAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Available bandwidth estimationOverheadInternet measurement toolsNetwork monitoringOverhead in available bandwidth estimation tools: Evaluation and analysisArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion1] E. Zhang, “Bandwidth Estimation for Virtual Networks,” PhD thesis, University of Nebraska Lincoln, 2015. [2] S. Baghermousavi, H. Rashidi, and H. Haghighi, “An approach to reduce qos monitoring overhead in ESB,” in e-Commerce in Developing Countries: With Focus on e-Trust (ECDC), 2014 8th International Conference on, pp. 1–5, 2014. [3] S. Lee, K. Levanti, and H. Kim, “Network monitoring: Present and future,” Computer Networks, Vol. 65, pp. 84 – 89, 2014. [4] A. Botta, A. Davy, B. Meskill, and G. Aceto, “Active techniques for available bandwidth estimation: Comparison and application,” in Data Traffic Monitoring and Analysis (E. Biersack, C. Callegari, and M. Matijasevic, eds.), Vol. 7754 of Lecture Notes in Computer Science, pp. 28–43, Springer Berlin Heidelberg, 2013. [5] M. Li, Y. Wu, and C. Chang, “Available bandwidth estimation for the network paths with multiple tight links and bursty traffic,” Journal of Network and Computer Applications, Vol. 36, no. 1, pp. 353 – 367, 2013. [6] S. Nam, S. Kim, S. Lee, and H. Kim, “Estimation of the available bandwidth ratio of a remote link or path segments,” Computer Networks, Vol. 57, no. 1, pp. 61–77, 2013. [7] C. Guerrero and M. Labrador, “A hidden markov model approach to available bandwidth estimation and monitoring,” in Internet Network Management Workshop, 2008. INM 2008. IEEE, pp. 1–6, 2008. [8] N. Jeyanthi, N. C. Iyengar, P. Kumar, and A. Kannammal, “An enhanced entropy approach to detect and prevent DDoS in cloud environment,” International Journal of Communication Networks and Information Security, Vol. 5, no. 2, pp. 110, 2013. [9] A. K. Paul, A. Tachibana, and T. Hasegawa, “Next: New enhanced available bandwidth measurement technique, algorithm and evaluation,” in 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC), pp. 443–447, IEEE, 2014. [10] K. Chan, “Testing and Measurement: Techniques and Applications,” Proceedings of the 2015 International Conference on Testing and Measurement Techniques (TMTA 2015), pp. 16-17, January 2015, Phuket Island, Thailand. CRC Press, 2015. [11] J. Kim and Y. Lee, “An end-to-end measurement and monitoring technique for the bottleneck link capacity and its available bandwidth,” Computer Networks, Vol. 58, pp. 158 – 179, 2014. [12] C. Guerrero and D. Morillo, “On the reduction of the available bandwidth estimation error through clustering with k-means,” in 2012 IEEE Latin-America Conference on Communications, pp. 1–5, 2012. [13] A. Ali, F. Michaut, and F. Lepage, “End-to-end available bandwidth measurement tools: A comparative evaluation of performances,” CoRR (Computing Research Repository), Vol. abs/0706.4004, p. 13, 2007. [14] G. Urvoy-Keller, T. En-Najjary, and A. Sorniotti, “Operational com parison of available bandwidth estimation tools,” SIGCOMM Comput. Commun. Rev. Vol. 38, pp. 39–42, 2008. [15] S. Nam, S. Kim, and D. Sung, “Estimation of available bandwidth for a queueing system,” Applied Mathematical Modelling, Vol. 33, no. 8, pp. 3299 – 3308, 2009. [16] C. Man, G. Hasegawa, and M. Murata, “A simultaneous inline measurement mechanism for capacity and available bandwidth of end to end network path,” IEICE TRANSACTIONS on Communications, Vol. E89-B No.9, pp. 2469 – 2479, 2006. [17] V. Ribeiro, R. Riedi, R. Baraniuk, J. Navratil, and L. Cottrell, “Pathchirp: Efficient available bandwidth estimation for network paths,” DARPA/AFRL, NSF, Texas Instruments, SLAC - Stanford, 2003. [18] R. Kapoor, C. Lao, L. Chen, Gerla, and Y. Sanadidi, “Capprobe: A simple and accurate capacity estimation technique,” in ACM SIGCOMM Computer Communication Review, Vol. 34, pp. 67–78, 2004. [19] C. Guerrero and M. Labrador, “Experimental and analytical evaluation of available bandwidth estimation tools,” in Local Computer Networks, Proceedings 2006 31st IEEE Conference on, pp. 710–717, 2006. [20] A. Shriram, M. Murray, Y. Hyun, N. Brownlee, A. Broido, M. Fomenkov, and K. Claffy, “Comparison of public end-to-end bandwidth estimation tools on high speed links,” in Proceedings of the 6th International Conference on Passive and Active Network Measurement, PAM’05, (Berlin, Heidelberg), pp. 306–320, 2005. [21] M. Jain and C. Dovrolis, “Ten fallacies and pitfalls on end-toend available bandwidth estimation,” in Proceedings of the 4th ACM SIGCOMM Conference on Internet Measurement, IMC ’04, (New York, NY, USA), pp. 272–277, 2004. [22] U. Nguyen, D. Tran, and G. Nguyen, “A taxonomy of applying filter techniques to improve the available bandwidth estimations,” in Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC ’14, (New York, NY, USA), pp. 18:1–18:8, 2014. [23] H. Zhou, Y. Wang, X. Wang, and X. Huai, “Difficulties in estimating available bandwidth,” in Communications, 2006. ICC ’06. 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Lowekamp, “Comparing passive network monitoring of grid application traffic with active probes,” in Proceedings of the 4th International Workshop on Grid Computing, GRID ’03-IEEE Computer Society, (Washington, DC, USA), pp. 84-91, 2003.PublicationORIGINALOverhead in Available Bandwidth Estimation.pdfOverhead in Available Bandwidth Estimation.pdfapplication/pdf1337534https://repositorio.cuc.edu.co/bitstreams/96942085-9456-40b9-a485-7884e79c0a8e/downloadb9972427b810f37fcf060b3dac634978MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/b6b73455-f8c3-4ad8-826d-6a15eefd7539/download8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILOverhead in Available Bandwidth Estimation.pdf.jpgOverhead in Available Bandwidth Estimation.pdf.jpgimage/jpeg85738https://repositorio.cuc.edu.co/bitstreams/20f08b64-f62b-4336-87e5-66d3e70f2050/downloada0db6d7c020e73bc62467fd8a59f11d8MD54TEXTOverhead in Available Bandwidth Estimation.pdf.txtOverhead in Available Bandwidth Estimation.pdf.txttext/plain60628https://repositorio.cuc.edu.co/bitstreams/056d1a76-2923-4157-a2a3-d737cbd8ce5b/download3b7866a068642d971d1ebe59289214f9MD5511323/2240oai:repositorio.cuc.edu.co:11323/22402024-09-17 14:06:25.339open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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