Estimating Available Bandwidth using End-To-End Delay Increase Rate
K. Uday Kumar Reddy1, G. Chennakesava Reddy2, M. Rudra Kumar3
1K.Uday Kumar Reddy, Associate Professor, Department of CSE, Annamacharya Institute of Technology & Sciences, Rajampet, Andhrapradesh, India-516126.
2G. Chennakesava Reddy, PG Student, Department of CSE, Annamacharya Institute of Technology & Sciences, Rajampet, Andhrapradesh, India-516126.
3M.Rudra Kumar, Professor & HOD, Department of CSE, Annamacharya Institute of Technology & Sciences, Rajampet, Andhrapradesh, India-516126.
Manuscript received on 24 August 2019. | Revised Manuscript received on 02 September 2019. | Manuscript published on 30 September 2019. | PP: 2234-2237 | Volume-8 Issue-11, September 2019. | Retrieval Number: K20510981119/2019©BEIESP | DOI: 10.35940/ijitee.K2051.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: For real-time services such as voice over internet protocol, video conferencing and peer-to-peer streaming, end-to-end bandwidth estimation is very essential. Several available techniques for estimating bandwidth have been suggested such as Magictrain, IGI / PTR, pathChirp, Yaz and ASSOLO. However, in terms of the accuracy of available bandwidth estimation and/or network load efficiency, these techniques have disadvantages. In this article, we present an available technique of estimating bandwidth consisting of two features to provide high accuracy estimation and low efficiency of network load. One feature is the accessible bandwidth assessment feature that uses the end-to-end delay increase rate to directly calculate the available bandwidth. The other feature is the rate adjustment algorithm which adjusts the mistake calculated using the available bandwidth assessment feature between the real accessible bandwidth and the accessible bandwidth. The suggested method’s rate adjustment algorithm is based on Magictrain’s because Magictrain offers high precision in estimating accessible bandwidth. Finally, in terms of estimation precision and network load efficiency, we compare the suggested technique with Magictrain using computer simulation and show the effectiveness of the suggested technique.
Keywords: Available bandwidth, queuing delay, rate adjustment, probe rate model.
Scope of the Article: