{"title":"Work With What You've Got: An Approach for Resource-Driven Adaptation","authors":"Paul A. Akiki, A. Zisman, A. Bennaceur","doi":"10.1109/ACSOS-C52956.2021.00030","DOIUrl":null,"url":null,"abstract":"Resource-driven systems are affected by resource variability, which prevents the timely completion of important tasks. This paper presents BOND, a hyBrid resOurce-driveN aDaptation approach which addresses the issue of resource variability by (i) prioritising tasks and making resources available for tasks with higher priorities, (ii) considering alternative task executions when resources are not available, (iii) substituting resources with alternative ones, and (iv) changing tasks into similar ones. The approach supports a proactive and reactive adaptation plan. A prototype tool has been implemented as a proof of concept and used for an initial evaluation of the approach in terms of its feasibility and scalability.","PeriodicalId":268224,"journal":{"name":"2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSOS-C52956.2021.00030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Resource-driven systems are affected by resource variability, which prevents the timely completion of important tasks. This paper presents BOND, a hyBrid resOurce-driveN aDaptation approach which addresses the issue of resource variability by (i) prioritising tasks and making resources available for tasks with higher priorities, (ii) considering alternative task executions when resources are not available, (iii) substituting resources with alternative ones, and (iv) changing tasks into similar ones. The approach supports a proactive and reactive adaptation plan. A prototype tool has been implemented as a proof of concept and used for an initial evaluation of the approach in terms of its feasibility and scalability.