COST MINIMIZATION MODEL FOR ONLINE SOCIAL NETWORKS IN GEO-DISTRIBUTED CLOUDS

Abstract The growth of internet services have greater impact among the social users. Cloud computing is the recent technology adopted by several Internet Service Providers (ISPs). Data center is the core part of the cloud technologies. Irrespective of different geographic locations, the data availability should be an easier process.Different sorts of system objectives can be addressed for data placement and replication process at different cloud servers.Social users have different proximities for every location. This paper resolves the data placement issue for Online Social Networks (OSN). Usually, the user's data are interconnected at different locations. Every read/write operations incur storage costs. Thus, we have proposed an enhanced costoptimization modelfor placing social media data which investigates the storage cost, redistribution cost and total estimated cost. Experimental analysis is carried out in Twitter dataset. The local information about the user i.e profile data and their connection details are collected for certain period of time. The cost is optimized from the throughput factor of the data placements over the cloud servers. Based on the geographical distance value, the user data are placed over the cloud servers. The cost is explored for one-time cost reduction and continuous cost reduction for inter-cloud . We have achieved 10% lesser cost than prior model. Keywords: Internet Service Providers, Data placement, Data replication, Data center, Inter-cloud and Cost optimization.