Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art | Paper Citation Record

Observation 8c0de71a-9e62-4518-931d-97cd23292c4d · outbound

This paper cites List scheduling algorithm for heterogeneous systems by an optimistic cost table.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art List scheduling algorithm for heterogeneous systems by an optimistic cost table

Reference 1

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Observation b5e2ff57-27e4-4078-990e-fdcbecf346d5 · outbound

This paper cites Flux: Overcoming scheduling challenges for exascale workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Flux: Overcoming scheduling challenges for exascale workflows

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.419524Z

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Observation 21829f40-6f56-49ed-ac70-8258ec992d4f · outbound

This paper cites Cost optimization approaches for scientific workflow scheduling in cloud and grid computing: A review, classifications, and open issues.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Cost optimization approaches for scientific workflow scheduling in cloud and grid computing: A review, classifications, and open issues

Reference 3

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Observation c66e2d72-7fa8-438f-a90f-74eaec9c3d9b · outbound

This paper cites Predicting dynamic memory requirements for scientific workflow tasks.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Predicting dynamic memory requirements for scientific workflow tasks

Reference 4

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Observation dd6ca5cd-a1f9-463c-827b-fc9c06f20479 · outbound

This paper cites Resilient scheduling of moldable parallel jobs to cope with silent errors.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Resilient scheduling of moldable parallel jobs to cope with silent errors

Reference 5

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Observation 61d808b4-cefe-4ffa-8d79-78924c84a1f7 · outbound

This paper cites Are user runtime estimates inherently inaccurate? In Job Scheduling Strategies for Parallel Processing: 10th International Workshop, JSSPP 2004, New York, NY, USA, June 13, 2004.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Are user runtime estimates inherently inaccurate? In Job Scheduling Strategies for Parallel Processing: 10th International Workshop, JSSPP 2004, New York, NY, USA, June 13, 2004

Reference 6

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Observation fe523764-898c-4b2a-a6fe-d2bfcaf6f630 · outbound

This paper cites Lotaru: Locally estimating runtimes of scientific workflow tasks in heterogeneous clusters.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Lotaru: Locally estimating runtimes of scientific workflow tasks in heterogeneous clusters

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.344337Z

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Observation af858534-cff1-4394-bcd4-53a2160e4163 · outbound

This paper cites Lotaru: Locally predicting workflow task runtimes for resource management on heterogeneous infrastructures.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Lotaru: Locally predicting workflow task runtimes for resource management on heterogeneous infrastructures

Reference 8

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Observation 72e647f8-f0aa-4982-945c-581ced8fd357 · outbound

This paper cites o er, Lauritz Thamsen, Bj \.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art o er, Lauritz Thamsen, Bj \

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.319690Z

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Observation 8be989a9-9edb-4f94-8db7-78e96ea76b05 · outbound

This paper cites Dynamic scheduling of a batch of parallel task jobs on heterogeneous clusters.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Dynamic scheduling of a batch of parallel task jobs on heterogeneous clusters

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.308288Z

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Observation 7e0a0dfb-2061-44c8-a6e3-5f064480f289 · outbound

This paper cites Dynamic dag scheduling under memory constraints for shared-memory platforms.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Dynamic dag scheduling under memory constraints for shared-memory platforms

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.294561Z

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Observation a9bd3e65-70b0-47ca-8467-e04d34acf305 · outbound

This paper cites Multi-criteria scheduling of pipeline workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Multi-criteria scheduling of pipeline workflows

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.281933Z

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Observation cf0cf4ca-c5d5-46de-aed4-fcfc11293cf4 · outbound

This paper cites Sizey: Memory-efficient execution of scientific workflow tasks.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Sizey: Memory-efficient execution of scientific workflow tasks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.268052Z

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Observation 69e7eb70-69a2-4036-8e48-8df9bedf208f · outbound

This paper cites Tarema: Adaptive Resource Allocation for Scalable Scientific Workflows in Heterogeneous Clusters.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Tarema: Adaptive Resource Allocation for Scalable Scientific Workflows in Heterogeneous Clusters

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.254868Z

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Observation 245cd2ab-fe0f-491b-8a4d-39f559e9d154 · outbound

This paper cites Leveraging reinforcement learning for task resource allocation in scientific workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Leveraging reinforcement learning for task resource allocation in scientific workflows

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.243340Z

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Observation 959c4daa-953b-417f-880d-d88536c49195 · outbound

This paper cites Chirkin, Adam S.Z.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Chirkin, Adam S.Z

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.229382Z

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Observation 59d890bd-c9d7-499e-a4e3-ff263f7951a5 · outbound

This paper cites Durillo, Vlad Nae, and Radu Prodan.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Durillo, Vlad Nae, and Radu Prodan

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.216463Z

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Observation 2aceff4a-b33f-4361-8d73-a67eac77844b · outbound

This paper cites Durillo, Radu Prodan, and Jorge G.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Durillo, Radu Prodan, and Jorge G

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.203781Z

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Observation 9882aace-582d-49e6-825c-98ba3b0b34a2 · outbound

This paper cites Toward fine-grained online task characteristics estimation in scientific workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Toward fine-grained online task characteristics estimation in scientific workflows

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.190257Z

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Observation fcbb6e5c-d873-4a9e-9057-316a726a738b · outbound

This paper cites Online task resource consumption prediction for scientific workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Online task resource consumption prediction for scientific workflows

Reference 20

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Observation af31551e-2d54-4026-b1a5-ef184e6e42f7 · outbound

This paper cites The nf-core framework for community-curated bioinformatics pipelines.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art The nf-core framework for community-curated bioinformatics pipelines

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.165346Z

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Observation aeaaf958-56d1-43d7-913b-f1b06a1d494c · outbound

This paper cites an unresolved cited work.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Unresolved cited work

Reference 22

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Observation 277428f3-fade-45da-a09e-6770ce632f60 · outbound

This paper cites CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:20:53.578887Z

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Observation f70b289a-c713-4baf-ad16-0ac6f34d34f0 · outbound

This paper cites Multiple workflow scheduling strategies with user run time estimates on a grid.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Multiple workflow scheduling strategies with user run time estimates on a grid

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.140662Z

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Observation bd34004b-2e3e-4ca6-9b13-7814e8abbbf8 · outbound

This paper cites Hanafy, Qianlin Liang, Noman Bashir, David Irwin, and Prashant Shenoy.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Hanafy, Qianlin Liang, Noman Bashir, David Irwin, and Prashant Shenoy

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.128278Z

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Observation d605bcff-08f4-412a-a48d-624b2c1d057f · outbound

This paper cites Task runtime prediction in scientific workflows using an online incremental learning approach.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Task runtime prediction in scientific workflows using an online incremental learning approach

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.116872Z

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Observation 8bb26d8e-0325-4a78-8290-b61e2a112a26 · outbound

This paper cites The impact of task runtime estimate accuracy on scheduling workloads of workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art The impact of task runtime estimate accuracy on scheduling workloads of workflows

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.105089Z

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Observation a8ae8efe-1905-4333-9075-13b14905e72c · outbound

This paper cites Mapping large memory-constrained workflows onto heterogeneous platforms.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Mapping large memory-constrained workflows onto heterogeneous platforms

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.092694Z

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Observation e6459996-9a8a-4369-b652-ac7d3eb8dee5 · outbound

This paper cites Ponder: Online Prediction of Task Memory Requirements for Scientific Workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Ponder: Online Prediction of Task Memory Requirements for Scientific Workflows

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.080734Z

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Observation 50dadc42-5816-4ffc-9007-9b21bf3afcfe · outbound

This paper cites How workflow engines should talk to resource managers: A proposal for a common workflow scheduling interface.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art How workflow engines should talk to resource managers: A proposal for a common workflow scheduling interface

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.066716Z

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Observation 78551127-21a6-4db6-8922-e1492dec3609 · outbound

This paper cites an unresolved cited work.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-16T05:20:54.053657Z

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Observation 79ec830e-e56b-4de2-ad2e-b7997bee4926 · outbound

This paper cites Multi-objective scheduling of scientific workflows in multisite clouds.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Multi-objective scheduling of scientific workflows in multisite clouds

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.042146Z

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Observation d1b29667-7517-4d63-8fda-8be0b825363b · outbound

This paper cites A survey of scheduling frameworks in big data systems.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art A survey of scheduling frameworks in big data systems

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.030122Z

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Observation 46709b12-5ba3-4c92-8a0b-ac489be7cf7d · outbound

This paper cites Scientific workflow scheduling with provenance data in a multisite cloud.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Scientific workflow scheduling with provenance data in a multisite cloud

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.018259Z

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Observation ced15a50-3736-4b04-a668-c5d7e9c1d9ad · outbound

This paper cites On the use of machine learning to predict the time and resources consumed by applications.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art On the use of machine learning to predict the time and resources consumed by applications

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:54.004221Z

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Observation 435dcb19-0650-4d87-a50a-59b444bee43a · outbound

This paper cites Scheduling multilevel deadline-constrained scientific workflows on clouds based on cost optimization.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Scheduling multilevel deadline-constrained scientific workflows on clouds based on cost optimization

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.990054Z

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Observation f49bf5d4-4b7c-47ce-8ead-bbcff8430e7b · outbound

This paper cites Execution time prediction for grid infrastructures based on runtime provenance data.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Execution time prediction for grid infrastructures based on runtime provenance data

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.978567Z

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Observation 8dbe8f4e-7b55-4a64-9659-8ff335c21e2e · outbound

This paper cites Optimizing job/task granularity for metagenomic workflows in heterogeneous cluster infrastructures.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Optimizing job/task granularity for metagenomic workflows in heterogeneous cluster infrastructures

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.965816Z

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Observation 808a069b-f908-453f-a5d3-6ee5a8cda934 · outbound

This paper cites Modeling and predicting execution time of scientific workflows in the grid using radial basis function neural network.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Modeling and predicting execution time of scientific workflows in the grid using radial basis function neural network

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.952084Z

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Observation dca3a06c-d98e-4e04-b5ac-06c207118e08 · outbound

This paper cites Ozkaya, Anne Benoit, Bora U c ar, Julien Herrmann, and \.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Ozkaya, Anne Benoit, Bora U c ar, Julien Herrmann, and \

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.940331Z

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Observation f75f5722-254a-46ac-94e5-de69cafb3bb7 · outbound

This paper cites Predicting workflow task execution time in the cloud using a two-stage machine learning approach.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Predicting workflow task execution time in the cloud using a two-stage machine learning approach

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.927929Z

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Observation 63d52c28-567c-402f-b627-c459ca2aba34 · outbound

This paper cites Not all tasks are created equal: Adaptive resource allocation for heterogeneous tasks in dynamic workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Not all tasks are created equal: Adaptive resource allocation for heterogeneous tasks in dynamic workflows

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.914461Z

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Observation ab021fac-f970-4e05-8db2-3c896dbfce7c · outbound

This paper cites Cost and time prediction for efficient execution of bioinformatics workflows in federated cloud.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Cost and time prediction for efficient execution of bioinformatics workflows in federated cloud

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.893291Z

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Observation ca867b73-b019-4c91-9723-561de5bbcb86 · outbound

This paper cites Carbon- Aware Computing for Datacenters.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Carbon- Aware Computing for Datacenters

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.880964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 16aca7e8-632e-407c-bd79-56174455fa46 · outbound

This paper cites A Multi-Objective Based Scheduling Framework for Effective Resource Utilization in Cloud Computing.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art A Multi-Objective Based Scheduling Framework for Effective Resource Utilization in Cloud Computing

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.868337Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2c9fc6e6-92e9-4e90-a4a0-c2ef18d7f1b7 · outbound

This paper cites Computational resource and cost prediction service for scientific workflows in federated clouds.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Computational resource and cost prediction service for scientific workflows in federated clouds

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.856707Z

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Observation 44f1b453-3bf7-41ee-ba6e-84cb652c28dc · outbound

This paper cites Adaptive resource allocation with job runtime uncertainty.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Adaptive resource allocation with job runtime uncertainty

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.845575Z

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Observation 6bcc4f54-a70b-4700-9ee0-a5c513f4510d · outbound

This paper cites Ecovisor: A virtual energy system for carbon-efficient applications.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Ecovisor: A virtual energy system for carbon-efficient applications

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.833686Z

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Observation b182e91a-e256-479e-824a-5759862dabc3 · outbound

This paper cites Dongarra.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Dongarra

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.820358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 66771ac7-6ccb-4204-af2e-5084c1bf847e · outbound

This paper cites Dynamic variant rank heft task scheduling algorithm toward exascle computing.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Dynamic variant rank heft task scheduling algorithm toward exascle computing

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.804867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0452714a-c9a2-4491-bbc8-24b59d37ae43 · outbound

This paper cites Cost-efficient task scheduling for executing large programs in the cloud.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Cost-efficient task scheduling for executing large programs in the cloud

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.787922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4c76cf1e-a6e8-4adc-a546-a0c5a7f2ed95 · outbound

This paper cites E-heft: Enhancement heterogeneous earliest finish time algorithm for task scheduling based on load balancing in cloud computing.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art E-heft: Enhancement heterogeneous earliest finish time algorithm for task scheduling based on load balancing in cloud computing

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.767384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0825abd0-f49e-4c01-b59b-d566a4abb259 · outbound

This paper cites A job sizing strategy for high-throughput scientific workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art A job sizing strategy for high-throughput scientific workflows

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.753750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a267476a-219e-4ef8-b30f-8b1d5dcbe30e · outbound

This paper cites Performance-effective and low-complexity task scheduling for heterogeneous computing.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Performance-effective and low-complexity task scheduling for heterogeneous computing

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.741183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3d20267d-c021-4222-b860-e8e096f6fed2 · outbound

This paper cites Performance-effective and low-complexity task scheduling for heterogeneous computing.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Performance-effective and low-complexity task scheduling for heterogeneous computing

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.728471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0c67719e-68ef-4a47-9937-28f05b32c9bc · outbound

This paper cites Dynamic task shaping for high throughput data analysis applications in high energy physics.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Dynamic task shaping for high throughput data analysis applications in high energy physics

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.715683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dbfc5b0e-e046-42fc-924c-21ad9a6863d4 · outbound

This paper cites Framework for automated partitioning and execution of scientific workflows in the cloud.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Framework for automated partitioning and execution of scientific workflows in the cloud

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.703145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation da924d0b-9b1e-4cee-909c-580a0745231f · outbound

This paper cites Predictive performance modeling for distributed batch processing using black box monitoring and machine learning.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Predictive performance modeling for distributed batch processing using black box monitoring and machine learning

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.690973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 288cba49-1a2e-4661-a286-7b9b7ecb9089 · outbound

This paper cites Let's wait awhile: How temporal workload shifting can reduce carbon emissions in the cloud.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Let's wait awhile: How temporal workload shifting can reduce carbon emissions in the cloud

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.678202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 80c27552-ab7d-49fb-a03a-f315678a3869 · outbound

This paper cites Zomaya, and Rajiv Ranjan.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Zomaya, and Rajiv Ranjan

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.663862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cd4a78be-9795-48fc-bb10-5143d9e67a44 · outbound

This paper cites Exploring the Potential of Carbon-Aware Execution for Scientific Workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Exploring the Potential of Carbon-Aware Execution for Scientific Workflows

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.650301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 561180ae-c6af-4374-bff0-d451eb81d268 · outbound

This paper cites Scientific workflow management: WASA architecture and applications.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Scientific workflow management: WASA architecture and applications

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.636705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 58594f41-3add-492f-bb2e-3f4025a74c26 · outbound

This paper cites Learning low-wastage memory allocations for scientific workflows at icecube.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Learning low-wastage memory allocations for scientific workflows at icecube

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.624089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4cac72e7-8fc0-47e8-8bab-6c245ee8f871 · outbound

This paper cites Feedback-based resource allocation for batch scheduling of scientific workflows.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Feedback-based resource allocation for batch scheduling of scientific workflows

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.606004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 326f8d9b-3191-49fe-985c-02e760410512 · outbound

This paper cites Cost and makespan-aware workflow scheduling in hybrid clouds.

Predicting the Performance of Scientific Workflow Tasks for Cluster Resource Management: An Overview of the State of the Art Cost and makespan-aware workflow scheduling in hybrid clouds

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:20:53.592572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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