Optimal negotiation of SLA in federated cloud using multiobjective genetic algorithms

Cloud providers nowadays are required to form a federation of clouds to remain competitive and gain share in the cloud service market. This provision is governed by service level agreement (SLA) to which both clients and providers are confined. Monitoring activities are undertaken to guarantee the pre agreed SLA and desired cloud quality of service (QoS). However, monitoring multiple SLAs in federated cloud depends highly on collaboration among cloud providers participating in satisfying client service request which makes it very challenging and complex. Monitoring linked SLAs requires consistent specification of SLA parameters, dynamic SLA negotiation and multi level SLA monitoring in addition to reliable enforcement measures. In this paper a novel approach for SLA negotiation in cloud environment using multi level genetic algorithms (MOGA) is presented. The efficiency of the framework lies in choosing the most optimized SLAs for inexperienced consumer or provider in federated cloud environment. This allows concurrency of SLAs from multiple providers increasing performance, reliability and scalability of applications.