Model-driven performance estimation, deployment, and resource management for cloud-hosted services

Authors:
Faruk Caglar;Kyoungho An;Shashank Shekhar;Aniruddha Gokhale
Affiliations:
Vanderbilt University, Nashville, TN, USA;Vanderbilt University, Nashville, TN, USA;Vanderbilt University, Nashville, TN, USA;Vanderbilt University, Nashville, TN, USA
Venue:
Proceedings of the 2013 ACM workshop on Domain-specific modeling
Year:
2013

Citing 4
Cited 0

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Abstract

There is a growing trend towards migrating applications and services to the cloud. This trend has led to the emergence of different cloud service providers (CSPs), in turn leading to different cost models offered by these CSPs to lease their resources, variabilities in the granularity and specification of resources provided, and heterogeneous APIs offered by the CSPs to the users to program resource requests and deployment for their cloud-hosted services. These challenges make it hard for customers of the cloud to seamlessly transition their services to the cloud or migrate between different CSPs. To address these challenges, this paper presents a solution based on model-driven engineering (MDE). Specifically, we describe the design of the domain-specific modeling languages in our MDE framework and the associated generative mechanisms that address the challenges related to estimating performance and cost to host the services in the cloud, automated deployment and resource management.