A Hybrid Model of Swarm Intelligence Algorithm to Improve the Hierarchical Cache Optimization in IPTV Networks

Abstract

In recent years, there has been an undeniable global leaning on developing Internet protocol television (IPTV) network amongst telecommunication companies because they have thought that IPTV is a new generation of TV industry. IPTV is a service for the delivery of broadcast TV, movies on demand services, end-to-end operator managed broadband IP data network with desired QoS to the public with a broadband Internet connection. Particle swarm optimization is a heuristic global optimization it comes from the study on the bird and fish flock movement behavior. In an IPTV network, Video on Demand and other video services produce a huge amount of unicast traffic from the Video Hub Office (VHO) to subscribers and, in turn, necessitate added bandwidth and equipment resources in the network. In order to minimize this traffic and overall cost of the network, a section of the video content is stored in caches closer to subscribers. In this paper, proposed a hybrid model of PSABC algorithm. The PSABC algorithm is a combination of Particle Swarm Algorithm (PSO) and Artificial Bee Colony (ABC) Algorithm. The approach is mainly used to find the optimal cache memory that should be assigned in order to attain maximum cost effectiveness. This proposed approach is used to attaining the optimal cache memory size which in turn minimizes the overall network cost. The proposed new swarm algorithm is very simple and very flexible when compared to the existing swarm based algorithms. The investigation shows that hierarchical distributed caching can save significant network cost through the utilization of the PSO algorithm. From the experimental results, it is concluded that the proposed algorithm can be used for solving dynamic optimization problems.