A constraints-based resource discovery model for multi-provider cloud environments

Abstract

Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services (such as network configuration or data replication) and operating costs (such as hosting cost and data throughput). Providers' cost models often change and new commodity cost models (such as spot pricing) can offer significant savings. In this paper, a software abstraction layer is used to discover the most appropriate infrastructure resources for a given application, by applying a two-phase constraints-based approach to a multi-provider cloud environment. In the first phase, a set of possible infrastructure resources is identified for the application. In the second phase, a suitable heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic may be most appropriate; for others a performance-based heuristic may be of greater relevance. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental results show that the proposed model can dynamically select appropriate resouces for an application's requirements.

Resource discovery for distributed computing systems: A comprehensive survey

“…Another example of resource discovery, for multi/many providers Clouds, is presented in Wright et al, [146]. It deploys a two-phase constraints-based resource discovery solution which uses a software abstraction layer to discover the most suitable infrastructure resources in a multi-provider Cloud environment for a given application request.…”

Application based brokering algorithm for optimal resource provisioning in multiple heterogeneous clouds

“…In recent years, researchers and cloud brokers have focused on developing models and methods for federated cloud service and product selection based on either minimizing the total deployment cost or maximizing the QoS. Cloud service provisioning and cost optimization based on static demand, price and availability have been discussed in [6][7][8][9][10][11], where [12,13] deal with the uncertainty in the demand, price and availability of cloud services.…”

“…The authors also considered the maximum number of resources provided by a single-cloud provider. Wright et al [11] introduced a two-phase constraint-based approach in a multi-cloud environment for discovering the most appropriate set of infrastructure resources for a given application. In the first phase, suitable resources are identified for the application, and in second phase, heuristic approach is used to select the best services based on cost and performance.…”

Equilibrium in cloud computing market

“…The public cloud computing market is still dominated by the services based on proprietary platforms and customer interfaces [1]. Under these kind of circumstances the customer expose switching costs and lock in to the cloud service provider [2].…”