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  1. Proceedings of the 2013 ACM workshop on Domain-specific modeling (DSM '13)
  2. Model-driven performance estimation, deployment, and resource management for cloud-hosted services
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MDE-based sensor management and verification for a self-driving miniature vehicle
Dynamic symbol templates and ports in MetaEdit+
Towards domain-specific property languages: the ProMoBox approach
Evaluating the benefits of using domain-specific modeling languages: an experience report
Model-driven performance estimation, deployment, and resource management for cloud-hosted services
model[NL]generation: natural language model extraction
Generating a ROS/JAUS bridge for an autonomous ground vehicle
A roadmap to domain specific programming languages for environmental modeling: key requirements and concepts
On the way of bottom-up designing textual domain-specific modelling languages
Empirical comparison of language workbenches
On the customization of model management systems for file-centric IDEs

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

Content Provider ACM Digital Library
Author An, Kyoungho Caglar, Faruk Gokhale, Aniruddha Shekhar, Shashank
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.
Starting Page 21
Ending Page 26
Page Count 6
File Format PDF
ISBN 9781450326001
DOI 10.1145/2541928.2541933
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2013-10-27
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Cloud computing Deployment Model-driven analysis
Content Type Text
Resource Type Article
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