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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. User-Centric Adaptation Analysis of Multi-Tenant Services
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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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User-Centric Adaptation Analysis of Multi-Tenant Services

Content Provider ACM Digital Library
Author García-galán, Jesús Trinidad, Pablo Ruiz-cortés, Antonio Pasquale, Liliana
Copyright Year 2016
Abstract Multi-tenancy is a key pillar of cloud services. It allows different users to share computing and virtual resources transparently, meanwhile guaranteeing substantial cost savings. Due to the tradeoff between scalability and customization, one of the major drawbacks of multi-tenancy is limited configurability. Since users may often have conflicting configuration preferences, offering the best user experience is an open challenge for service providers. In addition, the users, their preferences, and the operational environment may change during the service operation, thus jeopardizing the satisfaction of user preferences. In this article, we present an approach to support user-centric adaptation of multi-tenant services. We describe how to engineer the activities of the Monitoring, Analysis, Planning, Execution (MAPE) loop to support user-centric adaptation, and we focus on adaptation analysis. Our analysis computes a service configuration that optimizes user satisfaction, complies with infrastructural constraints, and minimizes reconfiguration obtrusiveness when user- or service-related changes take place. To support our analysis, we model multi-tenant services and user preferences by using feature and preference models, respectively. We illustrate our approach by utilizing different cases of virtual desktops. Our results demonstrate the effectiveness of the analysis in improving user preferences satisfaction in negligible time.
Starting Page 1
Ending Page 26
Page Count 26
File Format PDF
ISSN 15564665
e-ISSN 15564703
DOI 10.1145/2790303
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 User systems Human information processing Multi-tenant services
Content Type Text
Resource Type Article
Subject Control and Systems Engineering Software
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