Paper Citation Record · LEDGER

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

As of 8 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 2026-08-07T06:34:17.273281+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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: verified fuzzy; 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:52:57.535510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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

Resolution: unresolved; 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: verified fuzzy; 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: 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 2026-08-07T06:34:17.273281+00:00.

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: verified fuzzy; 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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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: verified fuzzy; 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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: verified fuzzy; 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: verified fuzzy; 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 2026-08-07T06:34:17.273281+00:00.

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

Resolution: verified fuzzy; 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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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: verified fuzzy; 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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.