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RESISTing reliability degradation through proactive reconfiguration

Published: 20 September 2010 Publication History

Abstract

Situated software systems are an emerging class of systems that are predominantly pervasive, embedded, and mobile. They are marked with a high degree of unpredictability and dynamism in the execution context. At the same time, such systems often need to satisfy strict reliability requirements. Most current software reliability analysis approaches are not suitable for situated software systems. We propose an approach geared to such systems, which continuously furnishes refined reliability predictions at runtime by incorporating various sources of information. The reliability predictions are leveraged to proactively place the software in the optimal configuration with respect to changing conditions. Our approach considers two representative architectural reconfiguration decisions that impact the system's reliability: reallocation of components to processes and changing the architectural style. We have realized the approach as part of a framework intended for mission-critical settings, called REsilient SItuated SofTware system (RESIST), and evaluated it using a mobile emergency response system.

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cover image ACM Conferences
ASE '10: Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering
September 2010
534 pages
ISBN:9781450301169
DOI:10.1145/1858996
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 20 September 2010

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Author Tags

  1. mobility
  2. reliability
  3. self-adaptation
  4. software architecture

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Overall Acceptance Rate 82 of 337 submissions, 24%

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Cited By

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  • (2022)Predictive Models in Software Engineering: Challenges and OpportunitiesACM Transactions on Software Engineering and Methodology10.1145/350350931:3(1-72)Online publication date: 9-Apr-2022
  • (2021)Toward Management of Uncertainty in Self-Adaptive Software Systems: IoT Case StudyComputers10.3390/computers1003002710:3(27)Online publication date: 27-Feb-2021
  • (2021)C-PO: A Context-Based Application-Placement Optimization for Autonomous Vehicles2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)10.23919/DATE51398.2021.9473948(1288-1293)Online publication date: 1-Feb-2021
  • (2020)BibliographyAn Introduction to Self‐Adaptive Systems10.1002/9781119574910.refs(241-262)Online publication date: 22-Oct-2020
  • (2019)Software Assurance in an Uncertain WorldFundamental Approaches to Software Engineering10.1007/978-3-030-16722-6_1(3-21)Online publication date: 4-Apr-2019
  • (2018)SATISFy: Towards a Self-Learning Analyzer for Time Series Forecasting in Self-Improving Systems2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems (FAS*W)10.1109/FAS-W.2018.00045(182-189)Online publication date: Sep-2018
  • (2018)Information Systems Architecture and Organization in the Era of MicroServicesNetwork, Smart and Open10.1007/978-3-319-62636-9_11(165-177)Online publication date: 7-Feb-2018
  • (2017)ReferencesSoftware Adaptation in an Open Environment10.1201/9781315181721-11(195-212)Online publication date: 28-Apr-2017
  • (2017)Self-adaptive Software Simulation: A Lighting Control System for Multiple DevicesModeling, Design and Simulation of Systems10.1007/978-981-10-6463-0_33(380-391)Online publication date: 26-Aug-2017
  • (2016)An Iterative Decision-Making Scheme for Markov Decision Processes and Its Application to Self-adaptive SystemsProceedings of the 19th International Conference on Fundamental Approaches to Software Engineering - Volume 963310.1007/978-3-662-49665-7_16(269-286)Online publication date: 2-Apr-2016
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