Fuzzy based dynamic load balancing scheme for efficient edge server selection in Cloud-oriented content delivery network using Voronoi diagram

Any given Euclidean space can be partitioned into non-overlapping regions using Voronoi diagram and the Delaunay triangulation connects sites using nearest-neighbor fashion. Realistically in this context, all the edge servers are scattered over the Earth surface and can be clustered using Voronoi diagram. Now nearest edge server selection by Delaunay triangulation over the Voronoi diagram is our prime target. Due to the large demand of Internet content coming from burst crowd, performance of the Cloud-oriented content delivery networks is drastically reduced. To improve the said performance degradation, nearest edge server selection is a primary goal of cloud service provider (like Akamai Technologies, Amazon CloudFront, Mirror Image Internet etc.). Empirically all the time load of the nearest edge server is not eligible for responding the user request. Therefore load balancing is also important criteria for selecting suitable edge server. In this paper, we have presented Fuzzy Based Least Response Time (FLRT) dynamic load balancing algorithm and which is effective for crisps input from different heterogeneous system. Thus, FLRT is a novel paradigm which can select nearest neighbor edge server from user´s current location where response time and load of the edge server is lowest.