Results 1 to 10 of about 105 (90)

An Autoscaling System Based on Predicting the Demand for Resources and Responding to Failure in Forecasting [PDF]

Sensors, 2023
In recent years, the convergence of edge computing and sensor technologies has become a pivotal frontier revolutionizing real-time data processing. In particular, the practice of data acquisition—which encompasses the collection of sensory information in
Jieun Park, Junho Jeong
doaj   +2 more sources

Proactive Autoscaling for Edge Computing Systems With Kubernetes [PDF]

Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion, 2021
With the emergence of the Internet of Things and 5G technologies, the edge computing paradigm is playing increasingly important roles with better availability, latency-control and performance. However, existing autoscaling tools for edge computing applications do not utilize heterogeneous resources of edge systems efficiently, leaving scope for ...
Prashant Singh, Salman Toor
exaly   +4 more sources

Graph-PHPA: Graph-Based Proactive Horizontal Pod Autoscaling for Microservices Using LSTM-GNN

2022 IEEE 11th International Conference on Cloud Networking (CloudNet), 2022
Microservice-based architecture has become prevalent for cloud-native applications. With an increasing number of applications being deployed on cloud platforms every day leveraging this architecture, more research efforts are required to understand how different strategies can be applied to effectively manage various cloud resources at scale.
Mingming Liu, Shaoshu Zhu
exaly   +4 more sources

AI-Driven Predictive Autoscaling in Kubernetes : Reinforcement Learning for Proactive Resource Optimization in Cloud-Native Environments

International Journal of Scientific Research in Computer Science Engineering and Information Technology, 2022
We propose a reinforcement learning-based autoscaling algorithm integrated with Karpenter on AWS EKS. Unlike threshold-based scaling, our method anticipates workload surges by analyzing historical patterns using predictive analytics, thereby reducing cloud spend and improving service availability. Simulations and real deployment benchmarks from Rialtic
Shiva Kumar Chinnam
exaly   +2 more sources

Time Series Forecasting-Based Kubernetes Autoscaling Using Facebook Prophet and Long Short-Term Memory

Frontiers in Computer Science
The advancement of cloud computing technologies has led to increased usage in application deployment in recent years. Kubernetes, a widely used container orchestration platform for deploying applications on cloud systems, provides benefits such as ...
Pasan Bhanu Guruge
exaly   +3 more sources

Horizontal Autoscaling of Virtual Machines in Hybrid Cloud Infrastructures: Current Status, Challenges, and Opportunities

Encyclopedia
The deployment of virtual machines (VMs) within the Infrastructure as a Service (IaaS) layer across public, private, or hybrid cloud infrastructures is prevalent in various organisational settings for hosting essential business services.
Kamran Munir, Zaheer Khan
exaly   +3 more sources

NimbusGuard: A Novel Framework for Proactive Kubernetes Autoscaling Using Deep Q-Networks

2026 40th International Conference on Information Networking (ICOIN)
Cloud native architecture is about building and running scalable microservice applications to take full advantage of the cloud environments. Managed Kubernetes is the powerhouse orchestrating cloud native applications with elastic scaling. However, traditional Kubernetes autoscalers are reactive, meaning the scaling controllers adjust resources only ...
Chamath Wanigasooriya, Indrajith Ekanayake   +1 more
exaly   +3 more sources

Proactive Random-Forest Autoscaler for Microservice Resource Allocation

IEEE Access, 2023
Cloud service providers have been shifting their workloads to microservices to take advantage of their modularity, flexibility, agility, and scalability. However, numerous obstacles remain to achieving the most out of microservice deployments, especially
Lamees M. Al Qassem, Thanos Stouraitis, Ernesto Damiani, Ibrahim Abe M. Elfadel   +3 more
doaj   +1 more source

Toward Optimal Load Prediction and Customizable Autoscaling Scheme for Kubernetes

Mathematics, 2023
Most enterprise customers now choose to divide a large monolithic service into large numbers of loosely-coupled, specialized microservices, which can be developed and deployed separately.
Subrota Kumar Mondal, Xiaohai Wu, Hussain Mohammed Dipu Kabir, Hong-Ning Dai, Kan Ni, Honggang Yuan, Ting Wang   +6 more
doaj   +1 more source

Graph neural networks for representing multivariate resource usage: A multiplayer mobile gaming case-study

International Journal of Information Management Data Insights, 2023
The emergence of Multiplayer Mobile Gaming (MMG) applications is intertwined with a plethora of Quality of Service and Quality of Experience requirements.
Theodoros Theodoropoulos, Antonios Makris, Ioannis Kontopoulos, John Violos, Przemysław Tarkowski, Zbyszek Ledwoń, Patrizio Dazzi, Konstantinos Tserpes   +7 more
doaj   +1 more source