Multi-objective Meta-heuristics for Scheduling Applications with High Availability Requirements and Cost Constraints in Multi-Cloud Environments

As the popularity of cloud computing increases, more and more applications are migrated onto them. Web 2.0 applications are the most common example of such applications. These applications require to scale, be highly available, fault tolerant and able to run uninterrupted for long periods of time (or even indefinitely). Moreover as new cloud providers appear there is a natural tendency towards choosing the best provider or a combination of them for deploying the application. Thus multi-cloud scenarios emerge from this situation. However, as multi-cloud resource provisioning is both complex and costly, the choice of which resources to lend and how to allocate them to application components needs to rely on efficient strategies. These need to take into account many factors including deployment and run-time cost, resource load, and application availability in case of failures. For this aim multi-objective scheduling algorithms seem an appropriate choice. This paper presents an algorithm which tries to achieve application high-availability and fault-tolerance while reducing the application cost and keeping the resource load maximized. The proposed algorithm is compared with a classic Round Robin strategy - used by many commercial clouds - and the obtained results prove the efficiency of our solution.