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Development of a YOLO-guided automated (microplastic) particle analysis workflow.

Anal Methods
Xie J, Gowen A, Xu JL.
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AMAS: Adaptive Auto-Scaling on the Edge

2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2021
Despite the emergence of edge computing as a key technology paradigm, there is a general lack of auto-scaling techniques specifically designed for edge computing applications. Further, existing auto-scaling solutions tailor-made for the cloud cannot be readily applied to an application running on an edge cluster. In this paper we present AMAS - a novel
Saptarshi Mukherjee, Subhajit Sidhanta
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Transforming reactive auto-scaling into proactive auto-scaling

Proceedings of the 3rd International Workshop on Cloud Data and Platforms, 2013
Elasticity is a key characteristic of cloud platforms enabling resource to be acquired on-demand in response to time-varying workloads. We introduce a new elasticity management framework that takes as input commonly used reactive rule-based scaling strategies but offers in return proactive auto-scaling.
Laura R. Moore, Kathryn Bean, Tariq Ellahi   +2 more
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A Virtualization Approach to Auto-Scaling Problem

2011 Eighth International Conference on Information Technology: New Generations, 2011
The paper proposes to simulate feasibility of using virtualization technology to auto-scaling problem in cloud computing. It uses ARENA simulation software to build two different models. There are auto-scaling without server virtualization and auto-scaling with server virtualization.
Theera Thepparat, Amnart Harnprasarnkit, Douanghatai Thippayawong, Veera Boonjing, Pisit Chanvarasuth   +4 more
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Auto scaling of containerized ACSs for CPE management

2016 18th Asia-Pacific Network Operations and Management Symposium (APNOMS), 2016
The increased popularity of over-the-top (OTT) services such as voice calls and text messaging popular has a great impact on the business of traditional telecom operations. It is important for a telecommunications company to maximize resource utilization so as to decrease OPEX/CAPEX (Operating Expense/Capital Expenditure).
Tse-Han Wang, Yen-Cheng Chen, Chen-Min Hsu, Kai-Sheng Hsu, Hey-Chyi Young   +4 more
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Auto-Scaling in the Cloud Environment

2020
Every software application has its own minimum set of requirements like CPU, storage, memory, networking, and power. These have to be integrated into a specific configuration to allow the smooth functioning of the software application. When data traffic becomes higher than expected, higher resources are required.
Ravindra Kumar Singh Rajput, Dinesh Goyal   +1 more
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Adaptive AI-based auto-scaling for Kubernetes

2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID), 2020
Kubernetes, the prevalent container orchestrator for cloud-deployed web applications, offers an automatic scaling feature for the application provider in order to meet the ever-changing amount of demand from its clients. This auto-scaling service, however, requires a seemingly difficult parameter set to be customized by the application provider, and ...
László Toka, Gergely Dobreff, Balázs Fodor, Balázs Sonkoly   +3 more
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An Auto-Scaling Framework for Heterogeneous Hadoop Systems

International Journal of Cooperative Information Systems, 2017
The scalability of the cloud infrastructure is essential to perform large-scale data processing using MapReduce programming model by automatically provisioning and de-provisioning the resources on demand. The existing MapReduce model shows performance degradation while getting adapted to heterogeneous environments since sufficient techniques are not ...
J. V. Bibal Benifa, Dejey
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Efficient Hybriding Auto-scaling for OpenStack Platforms

2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity), 2015
The use of virtualization technology has gradually changed the way a datacenter works in recent years. Nowadays the end-users of a datacenter do not access physical resources directly. Instead, they access virtualized resources, such as VMs and virtual clusters, on top of a pool of physical resources. This new computing paradigm provides the datacenter
Chia-Ching Chen, Shao-Jui Chen, Fan Yin, Wei-Jen Wang   +3 more
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