Content Delivery Networks

Author:

Zolfaghari Behrouz1,Srivastava Gautam2ORCID,Roy Swapnoneel3,Nemati Hamid R.4,Afghah Fatemeh5,Koshiba Takeshi6,Razi Abolfazl7,Bibak Khodakhast8,Mitra Pinaki1,Rai Brijesh Kumar1

Affiliation:

1. Indian Institute of Technology Guwahati, Assam, India

2. Brandon University Faculty of Science, Mathematics and Computer Science; Research Centre for Interneural Computing, China Medical University, Taichung, Taiwan

3. University of North Florida, FL, United States

4. University of North Carolina at Greensboro, NC, United States

5. Northern Arizona University, School of Informatics, Computing, and Cyber Systems, AZ, United States

6. Waseda University, Tokyo, Japan

7. Northern Arizona University, AZ, United States

8. Miami University, OH, United States

Abstract

Recently, Content Delivery Networks (CDN) have become more and more popular. The technology itself is ahead of academic research in this area. Several dimensions of the technology have not been adequately investigated by academia. These dimensions include outline management, security, and standardization. Discovering and highlighting aspects of this technology that may have or have not been covered by academic research is the first step toward helping academia bridge the gap with industry or even go one step further to lead industry in the right direction. This suggests a comprehensive survey on research works in this regard. The literature in this area has already come up with some surveys and taxonomies, but some of them are outdated or do not cover every aspect of CDN while others fail to detect existing trends or to develop a holistic roadmap for research on the technology. Furthermore, none of the existing surveys aim at enlightening the dark aspects of the technology that have not been subject to academic research. In this survey, we first extract the lifecycle of a CDN as suggested by the existing research. Then, we investigate previous relevant works on each phase of the lifecycle to clarify where the research is currently located and headed. We show how CDN technology tends to converge with emerging paradigms such as cloud computing, edge computing, and machine learning, which are more mature in terms of academic research. This helps us determine the right direction for further research by revealing the deficiencies in existing works.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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