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Paper Citation Record · LEDGER

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System

As of 9 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2505.23258.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.23258 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:52:53.017977Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

22 of 22 outbound references displayed

  • verified exact0
  • verified fuzzy15
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d196f077-9dd7-420b-bf53-7a8e49274a25 · outbound

This paper cites Domain-driven design for microser- vices: An evidence-based investigation.IEEE Transactions on Software Engineering, 2024.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Domain-driven design for microser- vices: An evidence-based investigation.IEEE Transactions on Software Engineering, 2024

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-07T12:52:58.277846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6bb863d4-e885-4d90-84ad-64775f4e5036 · outbound

This paper cites Drpc: Distributed reinforcement learning approach for scalable resource provisioning in container-based clusters.IEEE Transactions on Services Computing, 2024.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Drpc: Distributed reinforcement learning approach for scalable resource provisioning in container-based clusters.IEEE Transactions on Services Computing, 2024

Reference 2

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raw_fallback, observed 2026-08-07T12:52:57.885661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0c611c7a-1d18-4270-aea9-d2ce4cd5c779 · outbound

This paper cites Sealos: Develop, deploy, and scale in one seamless cloud platform.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Sealos: Develop, deploy, and scale in one seamless cloud platform

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 72a52795-35c1-4b40-81fc-f5096fcca977 · outbound

This paper cites an unresolved cited work.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Unresolved cited work

Reference 4

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unresolved
raw_fallback, observed 2026-08-07T12:52:57.235464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation fec288cc-15ff-4e54-ad91-71b090f47bff · outbound

This paper cites Deep learning with long short-term memory networks for financial market predictions.European Journal of Operational Research, 270(2):654–669, 2018.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Deep learning with long short-term memory networks for financial market predictions.European Journal of Operational Research, 270(2):654–669, 2018

Reference 5

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no resolver link, observed 2026-08-07T12:52:51.297433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d74f3ebf-73f4-4102-86cd-909627ee7814 · outbound

This paper cites A review of recurrent neural networks: Lstm cells and network architectures.Neural computation, 31(7):1235–1270, 2019.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System A review of recurrent neural networks: Lstm cells and network architectures.Neural computation, 31(7):1235–1270, 2019

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T12:52:51.396080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:52:51.396080Z digest=sha256:a327f0f44b84c8a262d1d7ea8190af4bf7ac3f931ba591a918338e92eccc6525

Observation 6ecff3e8-3e01-4d0f-8787-3f0071b4938a · outbound

This paper cites an unresolved cited work.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Unresolved cited work

Reference 7

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raw_fallback, observed 2026-08-07T12:52:56.929911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:51.486113Z digest=sha256:3458760688a5542545dd647b9b953b2ed4ae0cbadc5bcf4ecef79c7a24d6c887

Observation 83a78909-1b38-472c-a775-6263b11e03ec · outbound

This paper cites Toward highly scalable load balancing in kubernetes clusters.IEEE Communications Magazine, 58(7):78–83, 2020.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Toward highly scalable load balancing in kubernetes clusters.IEEE Communications Magazine, 58(7):78–83, 2020

Reference 8

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raw_fallback, observed 2026-08-07T12:52:56.653017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:51.588761Z digest=sha256:95252d9eb7b71ab5cd01f11272e346d8966c89c548abe114508db5ee7e1b3f0c

Observation eaac30d6-39f6-4e97-a808-e25e42f38f96 · outbound

This paper cites Arascaler: Adaptive resource autoscaling scheme using etimemixer for efficient cloud-native comput- ing.IEEE Transactions on Services Computing, PP:1–14, 01 2024.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Arascaler: Adaptive resource autoscaling scheme using etimemixer for efficient cloud-native comput- ing.IEEE Transactions on Services Computing, PP:1–14, 01 2024

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-07T12:52:56.346241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:51.718171Z digest=sha256:736215a9c75cbecd7cb3d33c092751d11ac35d32528681b61f5c208d1817cf50

Observation c1ff1390-e411-4089-96f3-a4d89c75f2fe · outbound

This paper cites Thangaraju.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Thangaraju

Reference 10

Resolution
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raw_fallback, observed 2026-08-07T12:52:56.063875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:51.787775Z digest=sha256:26f715abb9c3dbf459d3b4acd51c39d1045526c01843ae97a1515f11bf690b0a

Observation 98c0f45b-8eac-4c2c-96df-12332ebfe443 · outbound

This paper cites an unresolved cited work.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:52:55.732910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:51.880884Z digest=sha256:74b060e6865171fdc6d885dd2b47e526b70889d9c57ac3600b9dda8568a205be

Observation 2cf0fecd-d541-49c3-8328-9cc95051f101 · outbound

This paper cites Kubernetes scheduling: Taxonomy, ongoing issues and challenges.ACM Comput.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Kubernetes scheduling: Taxonomy, ongoing issues and challenges.ACM Comput

Reference 12

Resolution
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raw_fallback, observed 2026-08-07T12:52:55.480796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.028049Z digest=sha256:e2ae4432493b364343a1490963269f9e5577f57db04e988465d6c19bb722b5e4

Observation 0e6ab1f6-01cd-4b03-ae40-1d9a22adeabc · outbound

This paper cites an unresolved cited work.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:52:55.173077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.114298Z digest=sha256:2e57764978d69ebd79100bc81289c3ff5091f902f258009de6eeece30c5cba39

Observation 23ad9053-b62d-4e89-80b7-24c1e23b1ca9 · outbound

This paper cites Brownout approach for adaptive management of resources and applications in cloud computing systems: A taxonomy and future directions.ACM Comput.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Brownout approach for adaptive management of resources and applications in cloud computing systems: A taxonomy and future directions.ACM Comput

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:52:54.630130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.328876Z digest=sha256:1296ce8bacf5564b4eb41f799aecb4a921c4794f76bcf122fec8e4af4e6ec306

Observation 510945b1-ac7d-469d-93b3-34b9f3713d68 · outbound

This paper cites Machine learning-based orchestration of containers: A taxonomy and future directions.ACM Comput.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Machine learning-based orchestration of containers: A taxonomy and future directions.ACM Comput

Reference 15

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raw_fallback, observed 2026-08-07T12:52:54.451075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.428524Z digest=sha256:9609bb79e0fa7489bacc8949cf335cd3a2701bfd9f79ed31a703fed973be6116

Observation 2b53ce88-53d3-466c-8a22-8b354046a5fd · outbound

This paper cites Drs: A deep reinforcement learning enhanced kubernetes scheduler for microservice-based system.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Drs: A deep reinforcement learning enhanced kubernetes scheduler for microservice-based system

Reference 16

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raw_fallback, observed 2026-08-07T12:52:54.285379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.516630Z digest=sha256:ee4e09fe7ac6dc672278d694d1ace977b017f80738461883f7202b09d60d8111

Observation 9cb9ad5f-35c7-4165-968c-8a0b6b279c91 · outbound

This paper cites Noah: Reinforcement-learning-based rate limiter for microservices in large-scale e-commerce services.IEEE transactions on neural networks and learning systems, PP, 04 2023.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Noah: Reinforcement-learning-based rate limiter for microservices in large-scale e-commerce services.IEEE transactions on neural networks and learning systems, PP, 04 2023

Reference 17

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raw_fallback, observed 2026-08-07T12:52:54.021311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.612000Z digest=sha256:0bf5460011a4e3e1d549468a45f16161631f9a30fa7a99cfe05f998987e25636

Observation 39ad351b-526b-43fb-8c68-47f5a9fdee3a · outbound

This paper cites Deep reinforcement learning for multiobjective optimization.IEEE Transactions on Cybernetics, 51(6):3103–3114, 2021.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Deep reinforcement learning for multiobjective optimization.IEEE Transactions on Cybernetics, 51(6):3103–3114, 2021

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:52:53.831856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.726287Z digest=sha256:9491eeef47e5c54dd51acec103d6e54ed983f0896925ea8fcd2c10c1b82d834c

Observation 4dbffaa6-a67e-4a9d-b744-dd30433b3a69 · outbound

This paper cites Scaling container caching to larger networks with multi-agent reinforcement learning.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Scaling container caching to larger networks with multi-agent reinforcement learning

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:52:53.588883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.810324Z digest=sha256:b5ee4296c0839ba40af0c4613454fef9fa1bdc34e681083879ee2870571a9242

Observation e5c66139-1e9e-40a7-a321-1f446c45150c · outbound

This paper cites Proximal policy optimization with policy feedback.IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(7):4600–4610, 2021.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Proximal policy optimization with policy feedback.IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(7):4600–4610, 2021

Reference 20

Resolution
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raw_fallback, observed 2026-08-07T12:52:53.427746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.872662Z digest=sha256:bd4248f38cf2b4ac57963614593d4bc3fbc85c27d0655e17f337afc24ee88999

Observation 180c619c-ca88-4e96-aa78-a15acca1ee94 · outbound

This paper cites In- cremental least-recently-used algorithm: Good, robust, and predictable performance.IEEE Transactions on Mobile Computing, 2025.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System In- cremental least-recently-used algorithm: Good, robust, and predictable performance.IEEE Transactions on Mobile Computing, 2025

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:52:53.183345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:53.017977Z digest=sha256:6bec983edb7b1a660059bd123c9a07a5259f6d1374077bf1c1ea7ebabc0ccbcd

Observation 4e199637-0904-4791-afe3-bb6f47af3edb · outbound

This paper cites an unresolved cited work.

SealOS+: A Sealos-based Approach for Adaptive Resource Optimization Under Dynamic Workloads for Securities Trading System Unresolved cited work

Reference 235

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:52:54.859523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:52:52.215801Z digest=sha256:4d7e8ac9ac705bf7f484d77b8d79bc2943cd21407d101b9fd43dd58a2f5dc6b1

Pith citing papers

No inbound Pith citation observations are available.