Intelligent Horizontal Autoscaling in Edge Computing using a ...

3 Methods of “Auto” Scaling OpenShift Applications - Red Hat

Overview. As a developer, you can use a horizontal pod autoscaler (HPA) to specify how OpenShift Container Platform should automatically ...

Dynamically Scaling Video Inference at the Edge | Clear Linux* Project

Our use case combines edge computing and video inference. We explore how the new cloud-native architecture allows us use Kubernetes* pod scaling ...

Cloud-Native Processors and Edge Computing - phoenixNAP

Cloud-native edge apps often leverage rolling updates, a strategy that gradually replaces old instances with new versions. This tactic minimizes ...

Optimizing Parameters for Autoscaling of Serverless Edge Functions ...

Serverless Edge Computing [1], [2] can be a key enabler for emerging application paradigms, such as Edge. Intelligence [3], that require all resources in the ...

Find and explore academic papers | Connected ... - Connected Papers

Intelligent Horizontal Autoscaling in Edge Computing using a Double Tower Neural Network. John Violos, Stylianos Tsanakas, T. Theodoropoulos, Aris Leivadeas ...

Applications of AI in autoscaling of cloud infrastructure

Another area of development is the integration of AI with edge computing. As more processing moves to the edge of the network, AI will play a crucial role in ...

What are the recent advances in edge resource autoscaling? | 5 ...

Intelligent Horizontal Autoscaling in Edge Computing using a Double Tower Neural Network ... Intelligent Horizontal Proactive Autoscaling (IHPA) using a ...

Auto-scaling edge cloud for network slicing - NSF PAR

Dynamically reallocating computing resources to handle bursty workloads is a common practice for web applications (e.g., e-commerce) in clouds.

Horizontal-Autoscaling-Edge-Computing-DTNN/README.md at ...

Intelligent Horizontal Autoscaling in Edge Computing using a Double Tower Neural Network. The code expects a trainX list which consists of the numpy RNN ...

Edge Computing on Low Availability Devices with K3S in a Smart ...

In this paper, we present a system that uses K3S, a lightweight Kubernetes implementation, to orchestrate computing services onto low availability edge devices.

Smart HPA: A resource-efficient horizontal pod auto-scaler for ...

Auto-scaling is an essential requirement for microservice architectures as it allows a microservice to dynamically adjust its computing ...

Horizontal Pod autoscaling | Google Kubernetes Engine (GKE)

If you configure a workload to autoscale based on multiple metrics, the Horizontal Pod Autoscaler evaluates each metric separately and uses the scaling ...

Dynamic Resource Allocation for Containerized Applications in ...

Its native Horizontal Pod Autoscaler (HPA) mechanism is based ... Edge intelligence: paving the last mile of artificial intelligence with edge computing.

What is autoscaling? Cloud autoscaling explained - TechTarget

Autoscaling provides users with an automated approach to increase or decrease the compute, memory or networking resources they have allocated.

Smart Edge Computing: Optimizing the Entire Value Chain

Intelligent IoT edge concepts can be built with this approach. By using edge devices to process and analyze the growing volumes of data, the ...

Edge Computing for IoT‐Enabled Smart Grid - Wiley Online Library

Our survey deals with the integration of edge computing with IoT-based smart grid. ... Techniques of autoscaling can be horizontal, vertical, or ...

Edge Intelligence—Research Opportunities for Distributed ...

Terracciano, “KOSMOS: Vertical and horizontal resource autoscaling for Kubernetes,” in Service-Oriented Computing, vol. ... edge computing with deep reinforcement ...

Scaling Kubernetes | Spike Scaling | K8s Clust... - Avesha

Such automatic horizontal scaling, or autoscaling, drives the primary IaaS value proposition. Scaling out horizontally in the cloud is a simple ...

K-AGRUED: A Container Autoscaling Technique for Cloud-based ...

Most articles on proactive autoscaling in cloud computing have shortcomings in two ways. 1) During feature extraction, the temporal patterns of ...

Intelligent autoscaling in Kubernetes: the impact of container ... - DiVA

Cloud computing, container autoscaling, Optimering av resurser, Deep ... with respect to multiple performance metrics in the context of horizontal autoscaling ...