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Scale-Out vs. Scale-Up Techniques for Cloud Performance and Productivity
2014
2014 IEEE 6th International Conference on Cloud Computing Technology and Science
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An elastic cloud provisions machine instances upon user demand. Auto-scaling, scale-out, scale-up, or any mixture techniques are used to reconfigure the user cluster as workload changes. ...
We evaluate three scaling strategies to upgrade the performance, efficiency and productivity of elastic clouds like EC2, Rackspace, etc. ...
(c) Mixed Scaling-Out and Scaling-Up Technique: This refers to the use of both scale-out and scale-up techniques at the same time. ...
doi:10.1109/cloudcom.2014.66
dblp:conf/cloudcom/HwangSB14
fatcat:fnmnjmen2ngw5c5eushwyrs2jy
Cloud Performance Modeling with Benchmark Evaluation of Elastic Scaling Strategies
2016
IEEE Transactions on Parallel and Distributed Systems
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In this paper, we present generic cloud performance models for evaluating Iaas, PaaS, SaaS, and mashup or hybrid clouds. ...
To satisfy production services, the choice of scale-up or scale-out solutions should be made primarily by the workload patterns and resources utilization rates required. ...
up The performance maps of two HI Bench programs on two EC2 cluster configurations for the scale-out, scale-up, and mixed scale-up/scale-out workloads over 10 GB of data elements. ...
doi:10.1109/tpds.2015.2398438
fatcat:blkvz2kyuzfqpbfrlv4id2n54y
Scale-up vs scale-out for Hadoop
2013
Proceedings of the 4th annual Symposium on Cloud Computing - SOCC '13
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scale-up performance. ...
The conventional wisdom in industry and academia is that scaling out using a cluster of commodity machines is better for these workloads than scaling up by adding more resources to a single server. ...
Acknowledgments We thank the reviewers, and our shepherd Anthony Joseph, who provided valuable feedback and advice. ...
doi:10.1145/2523616.2523629
dblp:conf/cloud/AppuswamyGNHR13
fatcat:y6f5xc6plbarvpz7k6k2q3h46y
Using Cloud, Modularity, and Make-to-Upgrade Strategy for Integrating Customized-Oriented Supply Networks
[chapter]
2013
IFIP Advances in Information and Communication Technology
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The complementary aspects of these techniques are highlighted and briefly explained here. MTU is as a strategy for future products with new characteristics, e.g., upgradability. ...
As a practical solution, in this paper a new collaborative approach out of modularity structure, cloud computing, and a novel production strategy, called Make-to-Upgrade (MTU), is suggested. ...
Product Modularity and Make-To-Upgrade (MTU) Strategy In general, modularity in design of products brings about a large scale of product variety, while applying similar modules for alternative products ...
doi:10.1007/978-3-642-41266-0_53
fatcat:exljkcd5ifdrljf555i2fimebu
A Comparative Analysis of Traditional and Cloud Data Warehouse
2018
VAWKUM Transactions on Computer Sciences
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It can be scaled up or down at any time and also it has no limitation on increasing number of users. In this review paper, we have compared traditional and cloud data warehouse. ...
However, traditional data warehouse may not be suitable for the data analysis needs because of the evolving requirement of industry. It cannot be scaled up or down. ...
Figure- 2 : 2 Cloud Data Warehouse DW predicting the main source of decision support and business analytics.
Table 1 . 1 Traditional vs. Cloud DWH cannot scale data up and down at any time. ...
doi:10.21015/vtcs.v15i1.487
fatcat:473e2s7ygrgjxbegz2ecbohpee
Empirical prediction models for adaptive resource provisioning in the cloud
2012
Future generations computer systems
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Cloud computing allows dynamic resource scaling for enterprise online transaction systems, one of the key characteristics that differentiates the cloud from the traditional computing paradigm. ...
Experimental results demonstrate that the proposed technique offers more adaptive resource management for applications hosted in the cloud environment, an important mechanism to achieve ondemand resource ...
Acknowledgment NICTA is funded by the Australian Government as represented by the Department of Broadband, Communications and the Digital Economy and the Australian Research Council through the ICT Centre ...
doi:10.1016/j.future.2011.05.027
fatcat:rop4vny2bbduvd2ysv4gykujni
A Comparative study about Workload prediction from one time forecast with cyclic forecasts using ARIMA model for cloud environment
2018
EAI Endorsed Transactions on Energy Web
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1 Auto-scaling systems help provisioning resources on demand which helps tap into the elastic nature of the cloud. ...
To tackle provisioning resources on demand there are reactive and proactive strategies in place. ...
The result is that the scale up and the scale out combination gives the optimal scaling policy. ...
doi:10.4108/eai.13-7-2018.163977
fatcat:ixflog2vfbc3longlgclebfzuq
Validation of AIRS/AMSU cloud retrievals using MODIS cloud analyses
2005
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI
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This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. ...
Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and "effective" (product of infrared emissivity at 11 pm and physical cloud fraction ...
; 4) Update cloud clearing using AIRS regression guess parameters; for up to two
RESULTS First, we have performed collocated instantaneous retrieval intercomparisons using AIRS and MODIS measurements ...
doi:10.1117/12.603706
fatcat:uihibjbanjavtfnei4nnr4jknq
pipsCloud: High performance cloud computing for remote sensing big data management and processing
2018
Future generations computer systems
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To solve the aforementioned issues efficiently, we propose pipsCloud which combine recent Cloud computing and HPC techniques to enable large-scale RS data processing system as on-demand real-time services ...
improved data locality and optimized I/O performance. ...
From bottom to up is respectively physical resources, cloud framework, VE-RS, VS-RS, data management and cloud portal. ...
doi:10.1016/j.future.2016.06.009
fatcat:gnkwaeggozcenkbuw7vdbmhe7i
Lightweight Automatic Resource Scaling for Multi-tier Web Applications
2014
2014 IEEE 7th International Conference on Cloud Computing
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The most widely used and practical approach for dynamic scaling based on predefined policies (rules). ...
Our framework performs fine-grained vertical resource scaling of multi-tier web application. We present the design and implementation of VscalerLight. ...
Reactive mechanism allows to quickly scale up the VM resource assignment in response to unexpected load increase and provide desired performance. Our scaling framework runs on top of Xen hypervisor. ...
doi:10.1109/cloud.2014.69
dblp:conf/IEEEcloud/YazdanovF14
fatcat:sb5dtpanbfevhcheutvthnjns4
Comparison Between Measurements and WRF Numerical Simulation of Global Solar Irradiation in Romania
2013
Annals of West University of Timisoara: Physics
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(NMM) or GFS-WRF(ARW) is most suitable for short term global solar irradiation forecasting in order to assess the performance of the photovoltaic power stations (Badescu and Dumitrescu, 2012, [1], Martin ...
Based on a preliminary analysis that took into account several criteria among which, performance, cost, popularity and meteorological and satellite data accessibility we concluded that a combination GFS-WRF ...
In addition, statistical techniques have been proposed for forecasting solar irradiance with up to 24 h [4] . ...
doi:10.1515/awutp-2015-0103
fatcat:tcgibkrfxzbmrefw4ublmrodee
HeteroVisor
2015
SIGPLAN notices
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HeteroVisor is implemented for the Xen hypervisor, with mechanisms that go beyond core scaling to also deal with memory resources, via the online detection of hot memory pages and transparent page migration ...
The approach is explored for the heterogeneous processor and memory subsystems evolving for modern server platforms, leading to mechanisms that can manage these heterogeneous resources dynamically and ...
Both horizontal and vertical scaling are scale up methods, separate from the scale out methods varying the number VM instances. ...
doi:10.1145/2817817.2731191
fatcat:lefi7xjfenduvl7uhhvn7h6kgi
HeteroVisor
2015
Proceedings of the 11th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments - VEE '15
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HeteroVisor is implemented for the Xen hypervisor, with mechanisms that go beyond core scaling to also deal with memory resources, via the online detection of hot memory pages and transparent page migration ...
The approach is explored for the heterogeneous processor and memory subsystems evolving for modern server platforms, leading to mechanisms that can manage these heterogeneous resources dynamically and ...
Both horizontal and vertical scaling are scale up methods, separate from the scale out methods varying the number VM instances. ...
doi:10.1145/2731186.2731191
dblp:conf/vee/GuptaLS15
fatcat:fduahvnhbjdnnckqvf2gbnk7yu
ShuttleDB: Database-Aware Elasticity in the Cloud
2014
IEEE International Conference on Autonomic Computing
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We then combine these database-aware techniques with VM-level mechanisms to implement a flexible elasticity approach that can achieve efficient scale up, scale out, or scale back for diverse tenants with ...
Our experimental evaluation of the ShuttleDB prototype shows that by applying migration and replication techniques at the tenant level, automated elasticity can be achieved both intra-and inter-datacenter ...
, and scale-out or scale-up). ...
dblp:conf/icac/BarkerCHSC14
fatcat:5ssmuvkn25h2roh65f7pvxswry
Multi-Tenant Cloud Data Services: State-of-the-Art, Challenges and Opportunities
2022
Proceedings of the 2022 International Conference on Management of Data
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We discuss techniques that have been developed for enabling elasticity, providing SLAs, ensuring performance isolation, and reducing cost. ...
In this tutorial we review architectures of today's cloud data services and identify trends and challenges that arise in multi-tenant cloud data services. ...
better performance -without affecting performance of the production database. ...
doi:10.1145/3514221.3522566
fatcat:bnkqnk4j4zgvzkcyh2qs7skiqm
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