Content Delivery Network, or a CDN, is a globally distributed network of servers that helps provide good availability, faster and reliable performance, and security to the content distributors. In order to maintain a secure and reliable system any change proposed for the network needs to be thoroughly tested. But testing a full software release takes a lot of time because of a very huge database and complex dependencies between them. This increases the total time taken in the software development life cycle. In the existing system, a tester has to write test scripts for every Change Request (CR), which is a documented request to modify the current software system. This effort can be substantially reduced by developing a tool which can accurately test all the changes by dynamically generating test values for each metadata tag. (In this paper, the term “metadata tag” refers to settings used to control the configuration of web servers). This reduces the time to figure out all complex dependencies and test for each and every change made. The aim is to provide a simple, clean interface which allows the user to select a Change Request he wants to test and then dynamically generate positive and negative test values on which test will run on and provide a detailed result to the user whether the test passed or not.

Content Delivery Network; Metadata Tag; Change Request

[1] Q. Jia, R. Xie, T. Huang, J. Liu, and Y. Liu, "The Collaboration for Content Delivery and Network Infrastructures: A Survey," IEEE Access, vol. 5, pp. 18088-18106, 2017.
[2] K. Hosanagar, R. Krishnan, M. Smith and J. Chuang, "Optimal pricing of content delivery network (CDN) services," 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the, 2004, pp. 10 pp
[3] Pathan M, Buyya R. “A taxonomy of CDNs: In Content delivery networks,” 2008 (pp. 33-77), Springer, Berlin, Heidelberg.
[4] Stocker, Volker, Georgios Smaragdakis, William Lehr, and Steven Bauer. "The growing complexity of content delivery networks: Challenges and implications for the Internet ecosystem." Telecommunications Policy 41, no. 10 (2017): 1003-1016.
[5] G. Ma, Z. Chen, J. Cao, Z. Guo, Y. Jiang and X. Guo, "A tentative comparison on CDN and NDN," 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), San Diego, CA, 2014, pp. 2893- 2898.
[6] Pallis, George, and Athena Vakali. "Insight and perspectives for content delivery networks." Communications of the ACM49, no. 1 (2006): 101- 106.
[7] Garmehi, Mehran, Morteza Analoui, Mukaddim Pathan, and Rajkumar Buyya. "An economic replica placement mechanism for streaming content distribution in Hybrid CDN-P2P networks." Computer Communications 52 (2014): 60-70.
[8] Buyya, Rajkumar, Al-Mukaddim Khan Pathan, James Broberg, and Zahir Tari. "A case for peering of content delivery networks." arXiv preprint cs/0609027 (2006).
[9] Wang, Limin, Vivek Pai, and Larry Peterson. "The effectiveness of request redirection on CDN robustness." ACM SIGOPS Operating Systems Review 36, no. SI (2002): 345-360.
[10] Hu, Han, Yonggang Wen, Tat-Seng Chua, Zhi Wang, Jian Huang, Wenwu Zhu, and Di Wu. "Community based effective social video contents placement in cloud centric CDN network." In Multimedia and Expo (ICME), 2014 IEEE International Conference on, pp. 1-6. IEEE, 2014.
[11] Raciborski, Nathan F., and Bradley B. Harvell. "Write-cost optimization of CDN storage architecture." U.S. Patent 8,321,521 issued November 27, 2012.