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On the Value of Service Demand Estimation for Auto-scaling
2018In the context of performance models, service demands are key model parameters capturing the average time individual requests of different workload classes are actively processed. In a system under load, due to measurement interference, service demands normally cannot be measured directly, however, a number of estimation approaches exist based on high ...
André Bauer 0001 +3 more
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Auto-Scaling of Containers: The Impact of Relative and Absolute Metrics
2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W), 2017Today, The cloud industry is adopting the container technology both for internal usage and as commercial offering. The use of containers as base technology for large-scale systems opens many challenges in the area of resource management at run-time. This paper addresses the problem of selecting the more appropriate performance metrics to activate auto ...
Casalicchio, Emiliano +1 more
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Load Balancing and Auto Scaling in AWS
2023This chapter provides a thorough introduction to Autoscaling and Elastic Load Balancing (ELB) in the AWS cloud. It highlights the benefits of these services, which simplify workflows and automate tasks. The chapter offers an in-depth overview of ELB and Autoscaling, covering their basic uses and providing hands-on experience.
Parul Dubey +2 more
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Auto-scaling in the Cloud: Current Status and Perspectives
2019One of the main advantages of cloud computing is elasticity, which allows to rapidly expand or reduce the amount of leased resources in order to adapt to load variations, guaranteeing the desired quality of service. Auto-scaling is an extensively studied topic. Making optimal scaling choices is of paramount importance and can help reduce leasing costs,
Catillo M., Rak M., Villano U.
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Auto-Scaling Cloud-Based Memory-Intensive Applications
2020 IEEE 13th International Conference on Cloud Computing (CLOUD), 2020Today, Cloud providers offer simplistic scaling policies that rely on thresholds that force tenants to have a priori knowledge of their workloads. We develop a new method for scaling memory-intensive workloads that needs no thresholds. This makes it worry-free for tenants, and it adapts even as workloads evolve. This is especially hard for memory-bound
Joe H. Novak +2 more
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Kubernetes Advanced Auto Scaling Techniques
Journal of Mathematical & Computer Applications, 2022This paper discusses some sophisticated autoscaling strategies in Kubernetes, and they include horizontal and vertical pod autoscaling, cluster levels autoscaling, and metrics based autoscaling. In this regard, it covers the topics of both predictive and event-triggered auto scaling approaches and their applications, the advantages ...
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Cloud computing is gaining momentum as a subscription-oriented paradigm providing on-demand payable access to virtualized IT services and products across the net. It is a breakthrough technology that is offering on-demand access to various services across the network.
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Auto scaling of data plane VNFs in 5G networks
2017 13th International Conference on Network and Service Management (CNSM), 2017In order to meet the traffic demand from diverse next generation wireless network applications and exponentially increasing mobile subscriptions, various 5G network architectures are proposed by leveraging Software Defined Networking (SDN) and Network Function Virtualization (NFV) technologies.
Tulja Vamshi Kiran Buyakar +3 more
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Measuring Prediction Sensitivity of a Cloud Auto-scaling System
2014 IEEE 38th International Computer Software and Applications Conference Workshops, 2014Elasticity is one of the key benefits of cloud computing which helps customers reduce the cost. Although elasticity is beneficiary in terms of cost, obligation of maintaining Service Level Agreements leads to necessity in dealing with the cost-performance trade-off. Proactive auto-scaling is an efficient approach to overcome this problem.
Ali Yadavar Nikravesh +2 more
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Cloud Functions for Fast and Robust Resource Auto-Scaling
2019 11th International Conference on Communication Systems & Networks (COMSNETS), 2019We design and build FEAT, a new scaling approach that uses (1) cloud functions as interim processing resources to compensate for VM launch delays and (2) a reactive, knobless, auto-scaling algorithm that requires no pre-specified thresholds or parameters, making it robust against changing load.
Joe H. Novak +2 more
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