Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T15:11:00.112945Z
Paper Citation Record · LEDGER
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling
As of 23 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:2501.14456.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-13T03:25:27.105843Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T03:27:11.577995Z
Reference resolution
17 of 17 outbound references displayed
- verified exact0
- verified fuzzy17
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a2b7e849-db22-4276-86c6-28d1771ee129 · outbound
This paper cites Spark: Cluster Computing with Working Sets,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Spark: Cluster Computing with Working Sets,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.321225Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2aed2fea-f65c-48a8-85b4-06a21759cb73 · outbound
This paper cites Apache Flink™: Stream and Batch Processing in a Single Engine,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Apache Flink™: Stream and Batch Processing in a Single Engine,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.312762Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 6a4e274a-ea66-412d-8a66-1e6302551d1e · outbound
This paper cites AROMA: Automated Resource Allocation and Configuration of Mapreduce Environment in the Cloud,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling AROMA: Automated Resource Allocation and Configuration of Mapreduce Environment in the Cloud,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.303748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2e799f43-1ee9-44d0-a324-6d15030dd91b · outbound
This paper cites PerfOrator: Eloquent Performance Models for Resource Optimization,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling PerfOrator: Eloquent Performance Models for Resource Optimization,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.294717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1ab7d3f6-ee9f-4c97-b3d0-64c4ed6119ae · outbound
This paper cites Bubble-flux: Precise Online QoS Management for Increased Utilization in Warehouse Scale Computers,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Bubble-flux: Precise Online QoS Management for Increased Utilization in Warehouse Scale Computers,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.286261Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b5f738cf-ffd5-4970-85ba-cd59dde4f82c · outbound
This paper cites A Measurement Study of Server Utilization in Public Clouds,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling A Measurement Study of Server Utilization in Public Clouds,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.276671Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 785752f8-2bee-4a49-a027-c49d1129614c · outbound
This paper cites Quasar: Resource-efficient and QoS- aware Cluster Management,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Quasar: Resource-efficient and QoS- aware Cluster Management,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.266793Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 35ad9710-e37e-4af5-b00b-214bff6ffbff · outbound
This paper cites Scaling big data mining infrastructure: the twitter experience,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Scaling big data mining infrastructure: the twitter experience,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.254651Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 90fe6aa9-a73b-4ec3-96f1-8d00c32907ba · outbound
This paper cites Juggler: Autonomous Cost Optimization and Performance Prediction of Big Data Applications,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Juggler: Autonomous Cost Optimization and Performance Prediction of Big Data Applications,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.242643Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4065970d-5719-4556-bd9d-63c6f7a48543 · outbound
This paper cites Blink: Lightweight Sample Runs for Cost Optimization of Big Data Applica- tions,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Blink: Lightweight Sample Runs for Cost Optimization of Big Data Applica- tions,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.230624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b2aefc05-69c2-4a83-81a8-dc4b9208d2d5 · outbound
This paper cites Get Your Memory Right: The Crispy Resource Allocation Assistant for Large- Scale Data Processing,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Get Your Memory Right: The Crispy Resource Allocation Assistant for Large- Scale Data Processing,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.218548Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 235ff1d3-1d7d-4b31-ab0d-64d382e01549 · outbound
This paper cites Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.206721Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 0d7f9954-a890-42f8-bf2a-6ca583664c67 · outbound
This paper cites Ernest: Efficient Performance Prediction for Large-Scale Advanced Analytics,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Ernest: Efficient Performance Prediction for Large-Scale Advanced Analytics,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.194776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 16eb837b-725f-47fc-8ba8-d5fc8a11be97 · outbound
This paper cites CherryPick: Adaptively Unearthing the Best Cloud Con- figurations for Big Data Analytics,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling CherryPick: Adaptively Unearthing the Best Cloud Con- figurations for Big Data Analytics,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.183064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 557ab67e-a4a2-4125-80cb-339d7c19d22f · outbound
This paper cites Arrow: Low-Level Augmented Bayesian Optimization for Finding the Best Cloud VM,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Arrow: Low-Level Augmented Bayesian Optimization for Finding the Best Cloud VM,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.170864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2b037d83-99f3-4903-903e-49e50dfe8262 · outbound
This paper cites Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.159469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7cb20aad-fc45-46e3-a7be-f09d6aef50a9 · outbound
This paper cites Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs,.
Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling Towards Collaborative Optimization of Cluster Configurations for Distributed Dataflow Jobs,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:11:00.146888Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Pith citing papers
Observation f1f5ca19-da7b-4923-93af-2c8ab4c19ebe · inbound
BatchBench: Toward a Workload-Aware Benchmark for Autoscaling Policies in Big Data Batch Processing -- A Proposed Framework cites this paper.
BatchBench: Toward a Workload-Aware Benchmark for Autoscaling Policies in Big Data Batch Processing -- A Proposed Framework Experimentally Evaluating the Resource Efficiency of Big Data Autoscaling
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T03:27:11.580686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.