Analysis of Bargaining Game Policy in the Internet Content Distribution Chain

Introduction

In recent years, Internet traffic has undergone an inevitable and unlimited evolution and with the emergence of popular video streaming services that provide Internet videos on television and other terminals, CDNs (Content Delivery Network) have been considered as the dominant infrastructure for providing such content to end-users. The trends that Cisco (Cisco Visual Networking Index: Forecast and Methodology, 2016–2021, 2017) has forecast are: 70 percentage of all Internet traffic will go through CDNs by 2021, compared to 52 percentage in 2016 and 77 percentage of all Internet video traffic will cross CDNs in 2021, up from 67 percentage in 2016. This shows the importance of the actors that make it possible to provide internet content distribution networks in the chain of content delivery.

Content distribution and congestion limitation in the Internet network are the subject of much research in the field of telecommunication networks. This problem of congestion occurs when a content stored in the original server of the content provider is the subject of a very large number of requests. These studies are concentrated in order to reduce the response time (Latency) and thus ensure the content distribution with a better QoS to the end users, which surrounds the problem of traffic congestion in the network (Sahoo, Salahuddin, Glitho, Elbiaze, & Ajib, 2016). Among the most effective solutions is the use of content distribution networks as important actors in the content distribution chain. These networks consist of an original server connected to the other servers of content replication to hide the content requested by the population they cover. The basic operation mechanism of a Content Distribution Network (CDN) is the fact that first request on a content is served by the original server. This content will be transferred to the replica server placement that is in the area of the request coverage to serve future requests on the same content and it reduces the problem of congestion, which recurs in the network “backhaul” and improves the user QoS.

The content distribution networks’(CDN) customers are the end user, the content provider(CP), the Internet service providers, the mobile operators, ... etc (Pathan & Buyya, 2007). The end user is the entity that consumes the content (eg video, web page, music, ...) of the content provider. The content provider (for example: YouTube, Hulu, Dailymotion, ...) is the entity that owns the content or has obtained the rights to sell it. The CDN provider (for example: Akamai, Azure, Level 3 ...) is the entity that has replication servers in strategic locations and provides content delivery services to the content providers. Existing relationships between these actors are business relationships such as the purchase of content from a content provider (CP) by an end user. The costs of hosting the content by the (CDN) provider are paid by the content provider. These relationships have forced them to seek more satisfying services with moderately acceptable prices to earn profits to survive. This requires many studies in this area and our contribution falls within this framework.

In the Internet content distribution chain, the ecosystems analyzed each time resulted in the existence of a single content distribution network provider (CDN). This is strongly not the case because we currently notice the new several commercial (CDN)s and what represents a competitive environment since each one of them seeks to maximize its profit. Profit optimization is related to the strategy that each (CDN) provider seeks to achieve its objective. This depends on the price it offers content providers. The aim is to distribute their content and the QoS that is based on the size of the caches and the number of content replication servers exploited which meant the rate of coverage of user requests in different regions of the world.

To clarify the purpose of our research, this work aims to:

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  Resolve the conflict of actors selfish behavior presented in (Ait Omar, El Amrani, Baslam, & Fakir, 2019) by proposing the bargaining game solution;

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  Reformulate the new utility models after bargaining game by studying the existence and uniqueness of the Nash equilibrium;

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  Demonstrate that the bargaining game (cooperative game) is a beneficial strategy for all actors in the internet distribution chain.