Int. J. Advanced Networking and Applications Volume: 11 Issue: 01 Pages: 4155-4161(2019) ISSN: 0975-0290 4155 Dynamic Adaptive Streaming over HTTP (DASH) within P2P systems: a survey Koffka Khan Department of Computing and Information Technology the University of the West Indies, Trinidad and Tobago, W.I Email: koffka.khan@gmail.com Wayne Goodridge Department of Computing and Information Technology The University of the West Indies, Trinidad and Tobago, W.I Email: wayne.goodridge@sta.uwi.edu.com ---------------------------------------------------------------------- ABSTRACT----------------------------------------------------------- Video-over-IP applications have recently attracted a large number of users on the Internet. Traditional client- server based video streaming solutions incur lavish bandwidth provision cost on the server. Peer-to-Peer (P2P) networking is a new paradigm to build distributed network applications. Recently, several P2P streaming systems have been deployed to provide live and on-demand video streaming services on the Internet at low server cost. This paper explores dynamic adaptive streaming over HTTP (DASH) within P2P systems. Keywords – Video-over-IP; Internet; Peer-to-Peer; P2P; streaming; DASH. ------------------------------------------------------------------------------------------------------------------------------------------------- Date of Submission: Aug 30, 2018 Date of Acceptance: July 20, 2019 ------------------------------------------------------------------------------------------------------------------------------------------------- I. INTRODUCTION Peer-to-Peer (P2P) networking has recently emerged as a new paradigm to build distributed network applications. The basic design philosophy of P2P is to encourage users to act as both clients and servers, namely as peers. In a P2P network, a peer not only downloads data from the network, but also uploads the downloaded data to other users in the network. The uploading bandwidth of end users is efficiently utilized to reduce the bandwidth burdens otherwise placed on the servers. P2P file sharing applications, have been widely employed to quickly disseminate data files on the Internet [2]. More recently, P2P technology has been employed to provide media streaming services [17], [15]. Several P2P streaming systems have been deployed to provide on-demand or live video streaming services over the Internet. Streaming audio and video content currently accounts for the majority of the internet traffic and is typically deployed over the top of the existing infrastructure. We are facing the challenge of a plethora of media players and adaptation algorithms. With companies such as Netflix and YouTube accounting for more than 50% of the peak download traffic on North American fixed networks in 2015 video streaming represents a significant source of Internet traffic [10]. Dynamic adaptive streaming over HTTP (DASH) has recently emerged as a standard for Internet video streaming. A range of rate adaptation mechanisms are proposed for DASH systems in order to deliver video quality that matches the throughput of dynamic network conditions for a richer user experience. This work consists of four sections. Section II presents a categorization of DASH within P2P systems. Section III gives examples of DASH within P2P systems. Finally, the conclusion is given in Section IV. II. DASH WITHIN P2P SYSTEMS DASH within P2P systems are categorized into Overlay Nets, New Media, Collaborative, Multi-Source, Multicast, Switching, Caching and Incentive-based (see Figure 1). New Media is broken down into Multiview and 3D. Collaborative is broken down into Bottleneck Management. Finally, Pull-based is a component of Caching. Fig. 1. DASH within P2P systems. III. EXAMPLES OF DASH WITHIN P2P SYSTEMS A. Overlay Nets Authors present DONet, a data-driven overlay network for live media streaming [20]. The core operations in DONet are very simple: every node periodically exchanges data availability information with a set of partners, and retrieves unavailable data from one or more partners, or supplies available data to partners. Authors emphasize three salient features of this data-driven design: 1) easy to