SLA-Aware Application Deployment and Resource Allocation in Clouds

Provisioning resources as a service in a scalable on-demand manner is a basic feature in Cloud computing technology. Service provisioning in Clouds is based on Service Level Agreements (SLAs) representing a contract signed between the customer and the service provider stating the terms of the agreement including non-functional requirements of the service specified as Quality of Service (QoS), obligations, and penalties in case of agreement violations. On the one hand SLA violation should be prevented to avoid costly penalties and on the other hand providers have to efficiently utilize resources to minimize cost for the service provisioning. Thus, scheduling strategies considering multiple SLA parameters and efficient allocation of resources are necessary. Recent work considers various strategies with single SLA parameters. However, those approaches are limited to simple workflows and single task applications. Scheduling and deploying service requests considering multiple SLA parameters such as amount of CPU required, network bandwidth, memory and storage are still open research challenges. In this paper, we present a novel scheduling heuristic considering multiple SLA parameters for deploying applications in Clouds. We discuss in details the heuristic design and implementation and finally present detailed evaluations as a proof of concept emphasizing the performance of our approach.