ABR optimization for live sports events with ICN‐enabled network framework. Issue 5 (26th October 2020)

• Record Type: Journal Article
• Authors: Gao, Jianyue; Cui, Yiming
• Is Part Of: Internet technology letters. Volume 4:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-10-26
• Subjects: ABR optimization -- ICN -- neuronal population coding -- Q‐learning; Internet -- Periodicals; 004.67805
• DOI: 10.1002/itl2.249
• Languages: English
• ISSNs: 2476-1508

Abstract

Abstract : The global networked live sports businesses have been developed in the explosive mode, where the data retrieval of live video streaming has played the important role. Although some specialized techniques have been proposed to guarantee the effective video transmission, it is very necessary to pay attention to the Adaptive Bit Rate (ABR) optimization in order to enhance the quality of watching. In this paper, we use the Q‐learning method based on neuronal population coding to optimize ABR. Besides, we also introduce the Information Centric Networking (ICN) paradigm to improve the traditional distribution framework in order to store the hot sports streaming at the edge caches. We make the experiments by collecting the real live sports events, and the results show that the proposed scheme has better transmission time and quality of watching than the previous schemes.