Evaluating High Availability-Aware Deployments Using Stochastic Petri Net Model and Cloud Scoring Selection Tool

Abstract

Different challenges are facing the adoption of cloud-based applications, including high availability (HA), energy, and other performance demands. Therefore, an integrated solution that addresses these issues is critical for cloud services. Cloud providers promise the HA of their infrastructure while cloud tenants are encouraged to deploy their applications across multiple availability zones. Moreover, the environmental and cost impacts of running applications in the cloud are integral parts of incorporated responsibility where the cloud providers and tenants intend to reduce. Hence, an analytical stochastic model is needed for the tenants and providers to quantify the expected availability offered by an application deployment. If multiple deployment options can satisfy the HA requirement, the question remains, how can we choose the deployment that satisfies the other providers and tenants requirements Therefore, this paper proposes a cloud scoring system and integrates it with a Stochastic Petri Net model. While the Petri Net model evaluates the availability of cloud applications deployments, the scoring system selects the optimal HA-aware deployment in terms of energy, operational expenditure, and other norms. We illustrate our approach with a use case that shows how we can use the various deployment options to satisfy both the cloud tenant and provider needs.