Effective Bandwidth Prediction through Statistical Technique over Heterogeneous Networks
Renuka Deshpande1, Lata Ragha2, Satyendra Kumar Sharma3
1Renuka G. Deshpande*, Research Scholar, Pacific Academy of Higher Education and Research, Udaipur, India.
2Dr. Lata Ragha, Head of Department, Department of Computer Engineering at Fr. C. Rodrigues Institute of Technology, Vashi, Navi Mumbai, Maharashtra, India.
3Dr. Satyendra Kumar Sharma, Director, Modern Institute of Technology, Research Centre, Alwar, Rajasthan, India.
Manuscript received on September 17, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 508-512 | Volume-8 Issue-12, October 2019. | Retrieval Number: L3393081219/2019©BEIESP | DOI: 10.35940/ijitee.L3393.1081219
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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: Real time Streaming Media (Video Streaming) applications are mostly popular on the mobiles and computers using Internet. Due to higher demand of video streaming through wireless network and mobile devices, video are being transmitted through various heterogeneous networks so as to efficiently deliver to the clients devices. This has resulted in the lower quality of real time video, since real time streaming media has quality of parameter requirements like high bandwidth, low packet loss ratio, higher delay and jitter. Streaming media such as video through heterogeneous networks has more challenges due to unreliable wireless networks and device mobility; moreover bandwidth, delay and loss are unknown in advance and are unbounded. In this paper, effective bandwidth prediction through statistical technique over heterogeneous wireless communication networks is proposed. Statistical technique offers computationally efficient bandwidth prediction with reasonably better accuracy. Especially with mobile devices with limited computational power and battery life, necessitates better bandwidth prediction with efficient but computationally simpler algorithms. Bandwidth predictions assist in selecting effective network for video streaming when various heterogeneous networks are available. Detailed bandwidth prediction algorithm is presented with use of quality of service (QoS) parameters data sets available online.
Keywords: Bandwidth Prediction, Quality of Service Parameters, Statistical Technique, Heterogeneous Networks.
Scope of the Article: Heterogeneous Wireless Networks