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Towards Understanding the Usage Behavior of Google Cloud Users: The Mice and Elephants Phenomenon
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1017/cbo9781139939690openalex-snapshot
Workload Modeling for Computer Systems Performance Evaluation
inferredcites →https://doi.org/10.1109/aina.2012.106openalex-snapshot
Reliable Provisioning of Spot Instances for Compute-intensive Applications
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Evaluation on the Performance Fluctuation of Hadoop Jobs in the Cloud
inferredcites →https://doi.org/10.1109/icct.2010.5689022openalex-snapshot
Cloud Computing infrastructure for latency sensitive applications
inferredcites →https://doi.org/10.1109/icdcs.2012.52openalex-snapshot
Towards Optimal Capacity Segmentation with Hybrid Cloud Pricing
inferredcites →https://doi.org/10.1109/icpp.2013.56openalex-snapshot
Characterizing Cloud Applications on a Google Data Center
inferredcites →https://doi.org/10.1109/mascots.2006.30openalex-snapshot
Metrics for Mass-Count Disparity
inferredcites →https://doi.org/10.1109/noms.2012.6212064openalex-snapshot
Obfuscatory obscanturism: Making workload traces of commercially-sensitive systems safe to release
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Towards characterizing cloud backend workloads
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Heterogeneity and dynamicity of clouds at scale
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Fine-grained scheduling in multi-resource clusters
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Measuring data-centre workflows complexity through process mining: the Google cluster case
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Evaluation of Static Mapping for Dynamic Space-Shared Multi-task Processing on FPGAs
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Energy policies for data-center monolithic schedulers
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Optimistic scheduling with service guarantees
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Characterizing machines lifecycle in Google data centers
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SCORE: Simulator for cloud optimization of resources and energy consumption
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GAME-SCORE: Game-based energy-aware cloud scheduler and simulator for computational clouds
inferred← citeshttps://doi.org/10.1016/j.simpat.2019.101966openalex-snapshot
Sphere: Simulator of edge infrastructures for the optimization of performance and resources energy consumption
inferred← citeshttps://doi.org/10.1109/bigdata.2017.8258257openalex-snapshot
Imbalance in the cloud: An analysis on Alibaba cluster trace
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Exploring Characteristics of Inter-cluster Machines and Cloud Applications on Google Clusters
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Prediction-Based Admission Control for IaaS Clouds with Multiple Service Classes
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Cloud Workload Characterization and Profiling for Resource Allocation
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Towards Data-Driven Autonomics in Data Centers
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A Novel Classification Model to Predict Batch Job Failures in Co-located Cloud
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Measurement and Analysis of Cloud User Interest: A Glance From BitTorrent
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LAFS: Learning-Based Application-Agnostic Flow Scheduling for Datacenters
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Heterogeneous Task Co-location in Containerized Cloud Computing Environments
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Quality of Cloud Services Determined by the Dynamic Management of Scheduling Models for Complex Heterogeneous Workloads
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Google Users as Sequences: A Robust Hierarchical Cluster Analysis Study
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The Elasticity and Plasticity in Semi-Containerized Co-locating Cloud Workload
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Characterizing and orchestrating VM reservation in geo-distributed clouds to improve the resource efficiency
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A novel approach to workload prediction using attention-based LSTM encoder-decoder network in cloud environment
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Cloud failure prediction based on traditional machine learning and deep learning
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A User Relinquishment-based Resource Assignment Scheme to Maximize the Net Profit of Cloud Service Providers
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Efficient Orchestration of Distributed Workloads in Multi-Region Kubernetes Cluster
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Time Division Dominant Resource Allocation in Cloud Environments
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