Results 21 to 30 of about 3,474 (205)
Traffic-Aware Horizontal Pod Autoscaler in Kubernetes-Based Edge Computing Infrastructure
IEEE Access, 2022 Container-based Internet of Things (IoT) applications in an edge computing environment require autoscaling to dynamically adapt to fluctuations in IoT device requests.
Le Hoang Phuc, Linh-An Phan, Taehong Kim
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Proceedings of the Fifteenth European Conference on Computer Systems, 2020 In many public and private Cloud systems, users need to specify a limit for the amount of resources (CPU cores and RAM) to provision for their workloads. A job that exceeds its limits might be throttled or killed, resulting in delaying or dropping end-user requests, so human operators naturally err on the side of caution and request a larger limit than
Krzysztof Rzadca +10 more
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EdgeX over Kubernetes: Enabling Container Orchestration in EdgeX
Applied Sciences, 2021 With the exponential growth of the Internet of Things (IoT), edge computing is in the limelight for its ability to quickly and efficiently process numerous data generated by IoT devices.
Seunghwan Lee +4 more
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Proactive automatic up-scaling for Kubernetes
Adaptivni Sistemi Avtomatičnogo Upravlinnâ, 2023 Modern challenges in microservice architecture requires autoscaling (upscaling and down-scaling). As an example Black Friday can be considered when load to system increases significantly and obviously more computing capabilities are need to serve it ...
D. Gutman, O. Syrota
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Elascale: Autoscaling and Monitoring as a Service
CoRR, 2017 Auto-scalability has become an evident feature for cloud software systems including but not limited to big data and IoT applications. Cloud application providers now are in full control over their applications' microservices and macroservices; virtual machines and containers can be provisioned or deprovisioned on demand at runtime.
Hamzeh Khazaei +5 more
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Ruler Detection for Autoscaling Forensic Images [PDF]
International Journal of Digital Crime and Forensics, 2014 The assessment of forensic photographs often requires the calibration of the resolution of the image so that accurate measurements can be taken of crime-scene exhibits or latent marks. In the case of latent marks, such as fingerprints, image calibration to a given dots-per-inch is a necessary step for image segmentation, preprocessing, extraction of ...
Abhir Bhalerao, Gregory Reynolds
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Deep Learning-Based Autoscaling Using Bidirectional Long Short-Term Memory for Kubernetes
Applied Sciences, 2021 Presently, the cloud computing environment attracts many application developers to deploy their web applications on cloud data centers. Kubernetes, a well-known container orchestration for deploying web applications on cloud systems, offers an automatic ...
Nhat-Minh Dang-Quang, Myungsik Yoo
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A trace-based performance study of autoscaling workloads of workflows in datacenters [PDF]
, 2018 To improve customer experience, datacenter operators offer support for simplifying application and resource management. For example, running workloads of workflows on behalf of customers is desirable, but requires increasingly more sophisticated ...
Laurens Versluis +5 more
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Self-Adaptive Data Processing to Improve SLOs for Dynamic IoT Workloads
Computers, 2020 Internet of Things (IoT) covers scenarios of cyber−physical interaction of smart devices with humans and the environment and, such as applications in smart city, smart manufacturing, predictive maintenance, and smart home. Traditional scenarios are
Peeranut Chindanonda +2 more
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Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling [PDF]
Distributed dataflow systems like Spark and Flink enable data-parallel processing of large datasets on clusters. Yet, selecting appropriate computational resources for dataflow jobs is often challenging.
Thamsen, Lauritz +3 more
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