Genetic Algorithm Based Optimization in Peer to Peer Cloud Networks

Background & Objective: Cloud computing, a ubiquitous computing enables on demand access to resources in a pay - as - you - use trend. In cloud environment, the traffic is routed dynamically through different cloud service providers. Due to this, there is every possibility of optimization crunches, Quality of Service (QOS) contention and security breaches. For the routing to be efficient in cloud networks, there must be a proper tradeoff between QOS and security aspect. This paper presents a technique of using GA based approach in cloud network for QOS optimization of parameters like packet drop rate and hop count. GA is renowned of providing optimized solution for various wireless, adhoc networks, thus used in the proposed approach and also a comparison is made with the conventional routing approach. Conclusion: The results are being simulated on a MATLAB developed simulator and the results show that the proposed approach is providing better and optimized results when compared with conventional routing approach.