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SIP Diyalog Analitiği ve Ses Kaydı Ayrıştırılması Modeli

Yıl 2019, , 831 - 839, 25.12.2019
https://doi.org/10.19113/sdufenbed.578491

Öz

VoIP ve internet teknolojisindeki gelişmeler ve sunduğu avantajlar nedeniyle, internet üzerinden iletişim çok yaygın hale gelmiştir. Mevcutta kullanılan VoIP birimlerinin özellikle ses kayıt gibi I/O ağırlıklı işlemler sırasında o anki iletişim akışında duraklamalar ve bozulmalara neden olması nedeniyle, iletişimin I/O ağırlıklı işlemler düşünülerek yeniden tasarlanması gerekliliği ortaya çıkmıştır. Bu yayında iletişimin kayıt altına alınması ve ileride kullanıcıya ayrı bir döküm olarak sunulması üzerine karşılaşılan ölçekleme yetersizliklerinin çözümü üzerine bir model sunulmaktadır. İletişimin gerçekleştiği sunucu üzerinde iletişim ile beraber yapılan ses kaydında karşılaşılan sorunlar nedeniyle ortam ağ geçidi trafiğini yansıtma yöntemi ile başka bir sunucuya alınması ve analiz edilerek ses kaydının hangi kiracıya ve kime ait olduğunun tespit edilip eşleştirilerek kayıt edilmesi, ses formatı dönüşümünün yapılması ve kullanıcı ara yüzünden dinlenebilmesi yayın kapsamında incelenmiştir. Ayrıca birden çok işleyiciye adaptif olarak ölçeklenmesine imkan veren bir mimari sunulmuştur. Sunulan modelin programlanması ve işletilmesi sonucu aynı anda işlenebilen görüşme sayısında 5,33 kata kadar bir iyileştirme elde edilmiş, kayıt işlemlerinde yatay ölçekleme sağlanabilmiştir.

Destekleyen Kurum

Tübitak

Proje Numarası

7180242

Teşekkür

Bu proje Sanayi Bakanlığı'nın Ar-Ge merkezi bünyesinde sağlanan desteklerle ve TÜBİTAK TEYDEB 7180242 numaralı 1507 Kobi-ArGe projesi kapsamında gerçekleştirilmiştir.

Kaynakça

  • [1] SIP: Session initiation protocol, RFC 3261, http://www.ietf.org/rfc/rfc3261.txt (Erisim Tarihi: 15.05.2019).
  • [2] G.711 kodek bilgileri, https://www.itu.int/rec/T-RECG. 711/en (Erisim Tarihi: 15.05.2019).
  • [3] G.723 kodek bilgileri, https://www.itu.int/rec/T-RECG. 723.1/en (ErisimTarihi: 15.05.2019).
  • [4] G.726 kodek bilgileri, https://www.itu.int/rec/T-RECG. 726/en (Erisim Tarihi: 15.05.2019).
  • [5] G.729 kodek bilgileri, https://www.itu.int/rec/T-RECG. 729/en (Erisim Tarihi: 15.05.2019).
  • [6] Haloncn, T., Melero, 1. and Romero, J. 2002. GSM, GPRS and EDGE Performance: Evolution Toward 3GNMTS, Wiley & Sons.
  • [7] Järvinen, Kari. 2000. Standardisation of the adaptive multi-rate codec, 10th European Signal Processing Conference. IEEE, 2000.
  • [8] 3GPP TS 26,171: AMR Speech Codec; General description. https://www.3gpp.org/, (Erisim Tarihi: 15.05.2019).
  • [9] 3GPP TS 26.193 : AMR Wideband Speech Codec: Source Controlled Rate operation, https://www.3gpp.org/DynaReport/26193.htm, (Erisim Tarihi: 15.05.2019).
  • [10] Hoene, Christian, Holger Karl, and Adam Wolisz. 2004. A perceptual quality model for adaptive VoIP applications, Proceedings of SPECTS, Vol. 4.
  • [11] Chuah, C.-N. and Katz, R. H. 2002. Characterizing packet audio streams from internet multimedia applications. In Proceedings of IEEE International Conference on Communications (ICC 2002), volume 2, pages 1199-1203.
  • [12] Fukui, M., Shimauchi, S., Kobayashi, K., Hioka, Y., Ohmuro, H. 2014. Acoustic echo canceller software for VoIP hands-free application on smartphone and tablet devices. IEEE Transactions on Consumer Electronics, 60(3), 461-467.
  • [13] ETSI, EG. 202 396-1,Speech and multimedia transmission quality (STQ). 2011.
  • [14] Sfairopoulou, Anna, Carlos Macián, and Boris Bellalta. 2007. Dynamic measurement-based codec selection for VoIP in multirate IEEE 802.11WLANs.Proceedings of the 8th COST 290 Management Committee Meeting.
  • [15] Worrall, A.; Carter, B.;Widley, G. 2008. U.S. Patent No. 7,411,946. Washington, DC: U.S. Patent and Trademark Office.
  • [16] Zhang, Jian, and Andrew Moore. 2007. Traffic trace artifacts due to monitoring via port mirroring. Workshop on End-to-End Monitoring Techniques and Services. (pp. 1-8). IEEE.
  • [17] M. Arlitt and C. Williamson. 2005. An Analysis ofTCP Reset Behaviour on the Internet. ACM ComputerCommunication Review, Vol.35, No.1 pp.37-44.
  • [18] M. Arlitt, B. Krishnamurthy and J. C. Mogul. 2005.Predicting short-transfer latency from TCP arcana: Atrace-based validation. ACM/USENIX IMC’05, pp.213-226, Oct. 19-21.
  • [19] K.T. Chen, C.Y. Huang, P. Huang and C.L. Lei. 2006. Quantifying Skype User Satisfaction. ACM Sigcomm 2006, pp.399-410, Sept. 12-14.
  • [20] Callado, A. C., Kamienski, C. A., Szabó, G., Gero, B. P., Kelner, J., Fernandes, S. F., and Sadok, D. F. H. (2009). A survey on internet traffic identification. IEEE Communications Surveys and Tutorials, 11(3), 37-52.
  • [21] Barker, Kirk, and Darrell D. Roberts.2006. Voice over IP telephone recording architecture. U.S. Patent No. 7,054,420.
  • [22] Kouretas, Stephen, et al. 2011. Method and apparatus for voice-over-IP call recording and analysis. U.S. Patent No. 7,873,035.
  • [23] Martin, II James Paul. 2013. Distributed record server architecture for recording call sessions over a VoIP network. U.S. Patent No. 8,422,641.
  • [24] Clingenpeel, James E., and Brent E. Henry. 2012. Event monitoring and collection. U.S. Patent No. 8,122,122.
  • [25] Carroll, Robert, Darrell Roberts, and Theodore Edwards. 2009. System and method for on-demand recording. U.S. Patent No. 7,499,530.
  • [26] Silva, Christopher Anthony. 2013. Method for recording mobile phone calls. U.S. Patent No. 8,428,559.
  • [27] Othmer, Konstantin. 2012. Selectively buffering voice data at a server during a voice communication session. U.S. Patent No. 8,185,143.
  • [28] Ilan, Tomer, Eran Halbraich, and Ilan Yosef. 2018. Method and system for monitoring and recording voice from circuit-switched via a packet-switched network. U.S. Patent No. 7,333,445.
  • [29] Beuran, Razvan, and Mihai Ivanovici. 2004. Userperceived quality assessment for VoIP applications. CERN-OPEN-2004-007.
  • [30] Van Blarcum, Karen. 2004. Passive VoIP Call Recording. White Paper, http://www. audiocodes.com/library/type 39591 (Erisim Tarihi: 15.05.2019).
  • [31] Gao, Fuxiang, Yanfang Gao, and Miao Li. 2009. Design and implementation of web-based voip recording management system. International Conference on Information Science and Engineering. IEEE.
  • [32] Cordero, José Manuel, Manuel Dorado, and José Miguel de Pablo. 2012. Automated speech recognition in ATC environment. Proceedings of the 2nd International Conference on Application and Theory of Automation in Command and Control Systems. IRIT Press.
  • [33] SDP: Session Description Protocol, RFC 3261, https://tools.ietf.org/html/rfc4566 (Erisim Tarihi:15.05.2019).
  • [34] RTP: Real-Time Transport Protocol, RFC 3550, https://tools.ietf.org/html/rfc3550 (Erisim Tarihi: 15.05.2019).
  • [35] libpcap kütüphanesi, https://www.tcpdump.org/ (Erisim Tarihi: 15.05.2019).
  • [36] Programming with pcap,https://www.tcpdump.org/pcap.html (Erisim Tarihi:15.05.2019).

SIP Dialogue Analytics and Voice Record Decomposition Model

Yıl 2019, , 831 - 839, 25.12.2019
https://doi.org/10.19113/sdufenbed.578491

Öz


Due to the advancements in VoIP and internet technology and the advantages they offer, communication over the internet has adopted widespread. Due to the fact that the VoIP units used in the current process cause interruptions and distortions in the communication flow during the I/O-weighted operations such as voice recording, the necessity of redesigning the communication with I/O-weighted operations has emerged. In this publication, a model is presented on the solution of scaling deficiencies encountered upon recording the communication and presenting it as a separate casting to the user in the future. Due to the problems encountered in the recording of the communication on the same server where the communication is processed as well, forwarding to another server with the method of packet mirroring is studied. Further, analysis of the voice record to identify the tenant which the recording belongs to, matching the continous call information, recording the call, and converting to appropriate audio format are shown. The model offers an architecture that allows adaptive scaling to multiple processors. As a result of the presented model, an improvement of up to 5.33 was achieved in the number of simultaneous calls that can be achieved and horizontal scaling could be achieved among call recording processes.

Proje Numarası

7180242

Kaynakça

  • [1] SIP: Session initiation protocol, RFC 3261, http://www.ietf.org/rfc/rfc3261.txt (Erisim Tarihi: 15.05.2019).
  • [2] G.711 kodek bilgileri, https://www.itu.int/rec/T-RECG. 711/en (Erisim Tarihi: 15.05.2019).
  • [3] G.723 kodek bilgileri, https://www.itu.int/rec/T-RECG. 723.1/en (ErisimTarihi: 15.05.2019).
  • [4] G.726 kodek bilgileri, https://www.itu.int/rec/T-RECG. 726/en (Erisim Tarihi: 15.05.2019).
  • [5] G.729 kodek bilgileri, https://www.itu.int/rec/T-RECG. 729/en (Erisim Tarihi: 15.05.2019).
  • [6] Haloncn, T., Melero, 1. and Romero, J. 2002. GSM, GPRS and EDGE Performance: Evolution Toward 3GNMTS, Wiley & Sons.
  • [7] Järvinen, Kari. 2000. Standardisation of the adaptive multi-rate codec, 10th European Signal Processing Conference. IEEE, 2000.
  • [8] 3GPP TS 26,171: AMR Speech Codec; General description. https://www.3gpp.org/, (Erisim Tarihi: 15.05.2019).
  • [9] 3GPP TS 26.193 : AMR Wideband Speech Codec: Source Controlled Rate operation, https://www.3gpp.org/DynaReport/26193.htm, (Erisim Tarihi: 15.05.2019).
  • [10] Hoene, Christian, Holger Karl, and Adam Wolisz. 2004. A perceptual quality model for adaptive VoIP applications, Proceedings of SPECTS, Vol. 4.
  • [11] Chuah, C.-N. and Katz, R. H. 2002. Characterizing packet audio streams from internet multimedia applications. In Proceedings of IEEE International Conference on Communications (ICC 2002), volume 2, pages 1199-1203.
  • [12] Fukui, M., Shimauchi, S., Kobayashi, K., Hioka, Y., Ohmuro, H. 2014. Acoustic echo canceller software for VoIP hands-free application on smartphone and tablet devices. IEEE Transactions on Consumer Electronics, 60(3), 461-467.
  • [13] ETSI, EG. 202 396-1,Speech and multimedia transmission quality (STQ). 2011.
  • [14] Sfairopoulou, Anna, Carlos Macián, and Boris Bellalta. 2007. Dynamic measurement-based codec selection for VoIP in multirate IEEE 802.11WLANs.Proceedings of the 8th COST 290 Management Committee Meeting.
  • [15] Worrall, A.; Carter, B.;Widley, G. 2008. U.S. Patent No. 7,411,946. Washington, DC: U.S. Patent and Trademark Office.
  • [16] Zhang, Jian, and Andrew Moore. 2007. Traffic trace artifacts due to monitoring via port mirroring. Workshop on End-to-End Monitoring Techniques and Services. (pp. 1-8). IEEE.
  • [17] M. Arlitt and C. Williamson. 2005. An Analysis ofTCP Reset Behaviour on the Internet. ACM ComputerCommunication Review, Vol.35, No.1 pp.37-44.
  • [18] M. Arlitt, B. Krishnamurthy and J. C. Mogul. 2005.Predicting short-transfer latency from TCP arcana: Atrace-based validation. ACM/USENIX IMC’05, pp.213-226, Oct. 19-21.
  • [19] K.T. Chen, C.Y. Huang, P. Huang and C.L. Lei. 2006. Quantifying Skype User Satisfaction. ACM Sigcomm 2006, pp.399-410, Sept. 12-14.
  • [20] Callado, A. C., Kamienski, C. A., Szabó, G., Gero, B. P., Kelner, J., Fernandes, S. F., and Sadok, D. F. H. (2009). A survey on internet traffic identification. IEEE Communications Surveys and Tutorials, 11(3), 37-52.
  • [21] Barker, Kirk, and Darrell D. Roberts.2006. Voice over IP telephone recording architecture. U.S. Patent No. 7,054,420.
  • [22] Kouretas, Stephen, et al. 2011. Method and apparatus for voice-over-IP call recording and analysis. U.S. Patent No. 7,873,035.
  • [23] Martin, II James Paul. 2013. Distributed record server architecture for recording call sessions over a VoIP network. U.S. Patent No. 8,422,641.
  • [24] Clingenpeel, James E., and Brent E. Henry. 2012. Event monitoring and collection. U.S. Patent No. 8,122,122.
  • [25] Carroll, Robert, Darrell Roberts, and Theodore Edwards. 2009. System and method for on-demand recording. U.S. Patent No. 7,499,530.
  • [26] Silva, Christopher Anthony. 2013. Method for recording mobile phone calls. U.S. Patent No. 8,428,559.
  • [27] Othmer, Konstantin. 2012. Selectively buffering voice data at a server during a voice communication session. U.S. Patent No. 8,185,143.
  • [28] Ilan, Tomer, Eran Halbraich, and Ilan Yosef. 2018. Method and system for monitoring and recording voice from circuit-switched via a packet-switched network. U.S. Patent No. 7,333,445.
  • [29] Beuran, Razvan, and Mihai Ivanovici. 2004. Userperceived quality assessment for VoIP applications. CERN-OPEN-2004-007.
  • [30] Van Blarcum, Karen. 2004. Passive VoIP Call Recording. White Paper, http://www. audiocodes.com/library/type 39591 (Erisim Tarihi: 15.05.2019).
  • [31] Gao, Fuxiang, Yanfang Gao, and Miao Li. 2009. Design and implementation of web-based voip recording management system. International Conference on Information Science and Engineering. IEEE.
  • [32] Cordero, José Manuel, Manuel Dorado, and José Miguel de Pablo. 2012. Automated speech recognition in ATC environment. Proceedings of the 2nd International Conference on Application and Theory of Automation in Command and Control Systems. IRIT Press.
  • [33] SDP: Session Description Protocol, RFC 3261, https://tools.ietf.org/html/rfc4566 (Erisim Tarihi:15.05.2019).
  • [34] RTP: Real-Time Transport Protocol, RFC 3550, https://tools.ietf.org/html/rfc3550 (Erisim Tarihi: 15.05.2019).
  • [35] libpcap kütüphanesi, https://www.tcpdump.org/ (Erisim Tarihi: 15.05.2019).
  • [36] Programming with pcap,https://www.tcpdump.org/pcap.html (Erisim Tarihi:15.05.2019).
Toplam 36 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Adnan Ozsoy 0000-0002-0302-3721

Fatih Özdemir Bu kişi benim 0000-0003-0292-3602

Çağdaş Kopuz Bu kişi benim 0000-0002-3608-3747

Proje Numarası 7180242
Yayımlanma Tarihi 25 Aralık 2019
Yayımlandığı Sayı Yıl 2019

Kaynak Göster

APA Ozsoy, A., Özdemir, F., & Kopuz, Ç. (2019). SIP Diyalog Analitiği ve Ses Kaydı Ayrıştırılması Modeli. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 23(3), 831-839. https://doi.org/10.19113/sdufenbed.578491
AMA Ozsoy A, Özdemir F, Kopuz Ç. SIP Diyalog Analitiği ve Ses Kaydı Ayrıştırılması Modeli. Süleyman Demirel Üniv. Fen Bilim. Enst. Derg. Aralık 2019;23(3):831-839. doi:10.19113/sdufenbed.578491
Chicago Ozsoy, Adnan, Fatih Özdemir, ve Çağdaş Kopuz. “SIP Diyalog Analitiği Ve Ses Kaydı Ayrıştırılması Modeli”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 23, sy. 3 (Aralık 2019): 831-39. https://doi.org/10.19113/sdufenbed.578491.
EndNote Ozsoy A, Özdemir F, Kopuz Ç (01 Aralık 2019) SIP Diyalog Analitiği ve Ses Kaydı Ayrıştırılması Modeli. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 23 3 831–839.
IEEE A. Ozsoy, F. Özdemir, ve Ç. Kopuz, “SIP Diyalog Analitiği ve Ses Kaydı Ayrıştırılması Modeli”, Süleyman Demirel Üniv. Fen Bilim. Enst. Derg., c. 23, sy. 3, ss. 831–839, 2019, doi: 10.19113/sdufenbed.578491.
ISNAD Ozsoy, Adnan vd. “SIP Diyalog Analitiği Ve Ses Kaydı Ayrıştırılması Modeli”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 23/3 (Aralık 2019), 831-839. https://doi.org/10.19113/sdufenbed.578491.
JAMA Ozsoy A, Özdemir F, Kopuz Ç. SIP Diyalog Analitiği ve Ses Kaydı Ayrıştırılması Modeli. Süleyman Demirel Üniv. Fen Bilim. Enst. Derg. 2019;23:831–839.
MLA Ozsoy, Adnan vd. “SIP Diyalog Analitiği Ve Ses Kaydı Ayrıştırılması Modeli”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 23, sy. 3, 2019, ss. 831-9, doi:10.19113/sdufenbed.578491.
Vancouver Ozsoy A, Özdemir F, Kopuz Ç. SIP Diyalog Analitiği ve Ses Kaydı Ayrıştırılması Modeli. Süleyman Demirel Üniv. Fen Bilim. Enst. Derg. 2019;23(3):831-9.

e-ISSN :1308-6529
Linking ISSN (ISSN-L): 1300-7688

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