Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
×
Dec 1, 2022 · To optimize the efficiency of FaaS infrastructure, we introduce cloud-native server consolidation and propose DAC. DAC differentiates functions ...
DAC, a software-hardware co-design solu-tion to offer differentiated cloud-native server consolidation, is proposed and it is shown that DAC can improve the ...
In this paper, we analyze the invocation pattern of serverless functions and investigate its implications on server energy efficiency. Rather than using a one- ...
May 7, 2024 · Serverless computing has been adopted successfully in many application domains in the cloud [9] , but it is not yet fully developed at the edge ...
Missing: Consolidation | Show results with:Consolidation
Mar 10, 2021 · Serverless architecture is beneficial because you no longer purchase the expensive equipment or run the servers 24/7. On top of that, you are ...
Missing: Consolidation | Show results with:Consolidation
Characterizing and orchestrating NFV-ready servers for efficient edge data processing ... Cloud-native server consolidation for energy-efficient faas deployment.
Performance optimization for cloud computing systems in the microservice ... Cloud-native server consolidation for energy-efficient faas deployment. L ...
Dynamic consolidation of virtual machines (VMs) and switching idle nodes off allow Cloud providers to optimize resource usage and reduce energy consumption.
Guo, “Cloud-native server consolidation for energy-efficient faas deployment,” in Annual IFIP International Conference on Network and. Parallel Computing ...
Apr 3, 2023 · This enables orchestrators to perform optimal deployment choices, beyond the current solutions (based mainly on available CPU/memory on nodes), ...
Seamlessly Monitor, Manage and Gain Visibility of Your Distributed Compute Environment. Simplify...
Create, schedule & email out custom reports so you're always informed. Start a free trial.
With a cloud backup trial you can lift, shift or refactor workloads to and between clouds.