EFRRA: An Efficient Fault-Resilient-Replica-Algorithm for Content Distribution Networks

Nowadays, content distribution is an important peer-to-peer application on the Internet that has received considerable research attention. Content distribution applications typically allow personal computers to function in a coordinated manner as a distributed storage medium by contributing, searching, and obtaining digital content. The primary task in CDN is to replicate the contents over several mirrored web servers (i.e., surrogate servers) strategically placed at various locations in order to deal with the flash crowds. Geographically distributing the web servers’ facilities is a method commonly used by service providers to improve performance and scalability. Hence, contents in CDN are replicated in many surrogate servers according to some content distribution strategies dictated by the application environment. Devising an efficient and resilient content replication policy is crucial since, the content distribution can be limited by several factors in the network. Hence, we propose a novel Efficient Fault Resilient Replica Algorithm (EFRRA) to replicate the content from the origin server to a set of surrogate servers in an efficient and reliable manner. The contributions of this paper are twofold. First we introduce a novel EFRRA distribution policy and theoretically analyze its performance with traditional content replication algorithms. Then, by means of a simulation based performance evaluation, we assess the efficiency and resiliency of the proposed EFRR Algorithm, and compare its performance with traditional content replication algorithms stated in the literature. We demonstrate in experiment that EFRRA significantly reduces the file replication time and maintaining the Delivery ratio as compared with traditional strategies such as sequential unicast, multiple unicast, Fast Replica (FR), Resilient Fast Replica(R-FR), and Tornado codes (TC). This paper also analyzes the performance of sequential unicast, multiple unicast, Fast Replica (FR), Resilient Fast Replica(R-FR), Tornado codes, and EFRRA algorithms in terms of average replication time and maximum replication time.