Pub Date : 2018-10-03DOI: 10.1201/9781315221564-14
J. Sweitzer, C. Draper
{"title":"Architecture Overview for Autonomic Computing","authors":"J. Sweitzer, C. Draper","doi":"10.1201/9781315221564-14","DOIUrl":"https://doi.org/10.1201/9781315221564-14","url":null,"abstract":"","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81363862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-03DOI: 10.1201/9781315221564-18
Wusheng Chou
{"title":"A Control-Based Approach to Autonomic Performance Management in Computing Systems","authors":"Wusheng Chou","doi":"10.1201/9781315221564-18","DOIUrl":"https://doi.org/10.1201/9781315221564-18","url":null,"abstract":"","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74236978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-03DOI: 10.1201/9781315221564-22
{"title":"A Programming System for Autonomic Self-Managing Applications","authors":"","doi":"10.1201/9781315221564-22","DOIUrl":"https://doi.org/10.1201/9781315221564-22","url":null,"abstract":"","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74805976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-03DOI: 10.1201/9781315221564-17
R. Anthony, A. Butler, M. Ibrahim
{"title":"Exploiting Emergence in Autonomic Systems","authors":"R. Anthony, A. Butler, M. Ibrahim","doi":"10.1201/9781315221564-17","DOIUrl":"https://doi.org/10.1201/9781315221564-17","url":null,"abstract":"","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86519198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traffic experts try to optimise the signalisation of traffic light controllers during design-time based on historic traffic flow data. Traffic exhibits dynamic behaviour. Due to changing traffic demands, new and flexible traffic management systems are needed that optimise themselves during runtime. Organic Traffic Control is such a decentralised, self-organising system that adapts the green times of traffic lights to the current traffic conditions. Forecasts of future traffic conditions may result in a faster adaptation, higher robustness and flexibility. The combination of several forecasting techniques leads to fewer forecast errors. This paper presents three novel combination strategies from the machine learning domain using an Artificial Neural Network, Historic Load Curves and an Extended Classifier System.
{"title":"Learning a Dynamic Re-combination Strategy of Forecast Techniques at Runtime","authors":"M. Sommer, Sven Tomforde, J. Hähner","doi":"10.1109/ICAC.2015.70","DOIUrl":"https://doi.org/10.1109/ICAC.2015.70","url":null,"abstract":"Traffic experts try to optimise the signalisation of traffic light controllers during design-time based on historic traffic flow data. Traffic exhibits dynamic behaviour. Due to changing traffic demands, new and flexible traffic management systems are needed that optimise themselves during runtime. Organic Traffic Control is such a decentralised, self-organising system that adapts the green times of traffic lights to the current traffic conditions. Forecasts of future traffic conditions may result in a faster adaptation, higher robustness and flexibility. The combination of several forecasting techniques leads to fewer forecast errors. This paper presents three novel combination strategies from the machine learning domain using an Artificial Neural Network, Historic Load Curves and an Extended Classifier System.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"10 1","pages":"261-266"},"PeriodicalIF":0.0,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74582746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Motivated by the emergence of distributed clouds, we argue for the need for geo-elastic provisioning of application replicas to effectively handle temporal and spatial workload fluctuations seen by such applications. We present DBScale, a system that tracks geographic variations in the workload to dynamically provision database replicas at different cloud locations across the globe. Our geo-elastic provisioning approach comprises a regression-based model to infer the database query workload from observations of the spatially distributed front-end workload and a two-node open queueing network model to provision databases with both CPU and I/O-intensive query workloads. We implement a prototype of our DBScale system on Amazon EC2's distributed cloud. Our experiments with our prototype show up to a 66% improvement in response time when compared to local elasticity approaches.
{"title":"Model-Driven Geo-Elasticity in Database Clouds","authors":"Tian Guo, P. Shenoy","doi":"10.1109/ICAC.2015.46","DOIUrl":"https://doi.org/10.1109/ICAC.2015.46","url":null,"abstract":"Motivated by the emergence of distributed clouds, we argue for the need for geo-elastic provisioning of application replicas to effectively handle temporal and spatial workload fluctuations seen by such applications. We present DBScale, a system that tracks geographic variations in the workload to dynamically provision database replicas at different cloud locations across the globe. Our geo-elastic provisioning approach comprises a regression-based model to infer the database query workload from observations of the spatially distributed front-end workload and a two-node open queueing network model to provision databases with both CPU and I/O-intensive query workloads. We implement a prototype of our DBScale system on Amazon EC2's distributed cloud. Our experiments with our prototype show up to a 66% improvement in response time when compared to local elasticity approaches.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"43 1","pages":"61-70"},"PeriodicalIF":0.0,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80242493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christian Krupitzer, F. Roth, S. VanSyckel, C. Becker
Reusability of software artifacts reduces development time, effort, and error-proneness. Nevertheless, in the development of autonomic systems, developers often start from scratch when building a new system instead of reusing existing components. Many frameworks offer reusability on a higher level of abstraction, but neglect reusability on the lower component implementation level. In this short paper, we present a reusable adaptation logic by separating the generic structure and mechanisms of Autonomic Computing systems from its custom functionality. That is, we provide a reusable communication architecture with abstract component templates that enables a faster development and easier runtime adaptation. We evaluate our approach in a case study with two implementations.
{"title":"Towards Reusability in Autonomic Computing","authors":"Christian Krupitzer, F. Roth, S. VanSyckel, C. Becker","doi":"10.1109/ICAC.2015.21","DOIUrl":"https://doi.org/10.1109/ICAC.2015.21","url":null,"abstract":"Reusability of software artifacts reduces development time, effort, and error-proneness. Nevertheless, in the development of autonomic systems, developers often start from scratch when building a new system instead of reusing existing components. Many frameworks offer reusability on a higher level of abstraction, but neglect reusability on the lower component implementation level. In this short paper, we present a reusable adaptation logic by separating the generic structure and mechanisms of Autonomic Computing systems from its custom functionality. That is, we provide a reusable communication architecture with abstract component templates that enables a faster development and easier runtime adaptation. We evaluate our approach in a case study with two implementations.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"270 1 1","pages":"115-120"},"PeriodicalIF":0.0,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72861123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The issue we consider is how to gain the capability of useful self-improvement in systems that are expected to participate in various systems of systems during their lifetime. This is not the same as improvement in cyber physical systems (CPSs), even though large CPSs are systems of embedded systems. The difference is that we design and define the CPSs, so the integration onus is on us, not the systems and / or their components. In a System of Systems, we cannot define everything in advance, so the onus is on the participating systems. This paper is about designing systems so that they can help integrate, improve, and cooperatively improve themselves in a System of Systems that is unknown and unspecified at the time of their construction, and not completely known even during deployment.
{"title":"Designing Cooperating Self-Improving Systems","authors":"C. Landauer, K. Bellman","doi":"10.1109/ICAC.2015.71","DOIUrl":"https://doi.org/10.1109/ICAC.2015.71","url":null,"abstract":"The issue we consider is how to gain the capability of useful self-improvement in systems that are expected to participate in various systems of systems during their lifetime. This is not the same as improvement in cyber physical systems (CPSs), even though large CPSs are systems of embedded systems. The difference is that we design and define the CPSs, so the integration onus is on us, not the systems and / or their components. In a System of Systems, we cannot define everything in advance, so the onus is on the participating systems. This paper is about designing systems so that they can help integrate, improve, and cooperatively improve themselves in a System of Systems that is unknown and unspecified at the time of their construction, and not completely known even during deployment.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"8 1","pages":"273-278"},"PeriodicalIF":0.0,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82535390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Host-side SSD caches represent a powerful knob for improving and controlling storage performance and improve performance isolation. We present Centaur, as a host-side SSD caching solution that uses cache sizing as a control knob to achieve storage performance goals. Centaur implements dynamically partitioned per-VM caches with per-partition local replacement to provide both lower cache miss rate, better performance isolation and performance control for VM workloads. It uses SSD cache sizing as a universal knob for meeting a variety of workload-specific goals including per-VM latency and IOPS reservations, proportional share fairness, and aggregate optimizations such as minimizing the average latency across VMs. We implemented Centaur for the VMware ESX hyper visor. With Centaur, times for simultaneously booting 28 virtual desktops improve by 42% relative to a non-caching system and by 18% relative to a unified caching system. Centaur also implements per-VM shares for latency with less than 5% error when running micro benchmarks, and enforces latency and IOPS reservations on OLTP workloads with less than 10% error.
{"title":"Centaur: Host-Side SSD Caching for Storage Performance Control","authors":"Ricardo Koller, A. Mashtizadeh, R. Rangaswami","doi":"10.1109/ICAC.2015.44","DOIUrl":"https://doi.org/10.1109/ICAC.2015.44","url":null,"abstract":"Host-side SSD caches represent a powerful knob for improving and controlling storage performance and improve performance isolation. We present Centaur, as a host-side SSD caching solution that uses cache sizing as a control knob to achieve storage performance goals. Centaur implements dynamically partitioned per-VM caches with per-partition local replacement to provide both lower cache miss rate, better performance isolation and performance control for VM workloads. It uses SSD cache sizing as a universal knob for meeting a variety of workload-specific goals including per-VM latency and IOPS reservations, proportional share fairness, and aggregate optimizations such as minimizing the average latency across VMs. We implemented Centaur for the VMware ESX hyper visor. With Centaur, times for simultaneously booting 28 virtual desktops improve by 42% relative to a non-caching system and by 18% relative to a unified caching system. Centaur also implements per-VM shares for latency with less than 5% error when running micro benchmarks, and enforces latency and IOPS reservations on OLTP workloads with less than 10% error.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"69 1","pages":"51-60"},"PeriodicalIF":0.0,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86807329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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