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  1. Transactions on Autonomous and Adaptive Systems (TAAS)
  2. ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 10
  3. Issue 4(Special Section on Best Papers from SEAMS 2014 and Regular Articles), February 2016
  4. Designing Adaptive Applications Deployed on Cloud Environments
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ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 11
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 10
Issue 4(Special Section on Best Papers from SEAMS 2014 and Regular Articles), February 2016
Introduction to the Special Section on Best Papers from SEAMS 2014
Analyzing Latency-Aware Self-Adaptation Using Stochastic Games and Simulations
User-Centric Adaptation Analysis of Multi-Tenant Services
Designing Adaptive Applications Deployed on Cloud Environments
Inferring Software Component Interaction Dependencies for Adaptation Support
Just-in-Time Adaptive Algorithm for Optimal Parameter Setting in 802.15.4 WSNs
Connectivity Reestablishment in Self-Organizing Sensor Networks with Dumb Nodes
Self-Stabilized Fast Gossiping Algorithms
Enhancing Reliability of Workflow Execution Using Task Replication and Spot Instances
Issue 3, October 2015
Issue 2, June 2015
Issue 1, March 2015
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 9
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 8
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 7
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 6
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 5
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 4
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 3
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 2
ACM Transactions on Autonomous and Adaptive Systems (TAAS) : Volume 1

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Designing Adaptive Applications Deployed on Cloud Environments

Content Provider ACM Digital Library
Author Zoghi, Parisa Ghanbari, Hamoun Litoiu, Marin Shtern, Mark
Copyright Year 2016
Abstract Designing an adaptive system to meet its quality constraints in the face of environmental uncertainties can be a challenging task. In a cloud environment, a designer has to consider and evaluate different control points, that is, those variables that affect the quality of the software system. This article presents a methodology for designing adaptive systems in cloud environments. The proposed methodology consists of several phases that take high-level stakeholders’ adaptation goals and transform them into lower-level MAPE-K loop control points. The MAPE-K loops are then activated at runtime using search-based algorithms. Our methodology includes the elicitation, ranking, and evaluation of control points, all meant to enable a runtime search-based adaptation. We conducted several experiments to evaluate the different phases of our methodology and to validate the runtime adaptation efficiency.
Starting Page 1
Ending Page 26
Page Count 26
File Format PDF
ISSN 15564665
e-ISSN 15564703
DOI 10.1145/2822896
Volume Number 10
Issue Number 4
Journal ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-01-13
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Adaptive systems Cloud computing Design Performance
Content Type Text
Resource Type Article
Subject Control and Systems Engineering Software
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