Pith. sign in

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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:50.982955Z digest=sha256:4f15542af2ff241606f4d3a9a280ce03b4c47487a0a6076e39cfdc1c7e764e8d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:51.072116Z digest=sha256:d183265cc6db8bce2f9b051b76de247ca2ba491834411da68f287d4c337f9a6a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:51.143826Z digest=sha256:b87ca799ebfa7d290e2ec5820f2515928897abeeaf7a2ac4a9fc1692c678899a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:51.202977Z digest=sha256:8845ab59abc96ed5ef4e6e1ba666b5198e737b209d72aba144a95fff1317f938

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.

source=pdf_text observed=2026-08-07T12:52:51.297433Z digest=sha256:4f46e35b713dd458e59c1b422028ca921d770361d24be55bc993f99427cb09b9

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

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:51.486113Z digest=sha256:baa307c327c412e7845cdc1bef015bb09cc736218187d401b706f25ba798aa47

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:51.588761Z digest=sha256:556dedc4f50811478f841a83ae1efe32c604ffcb705776b7bbbe5079f6275b22

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:51.718171Z digest=sha256:93aeaf014ed9c1688c4bb072a4dd23c87c263d5e044c431aead848d689064d50

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:51.787775Z digest=sha256:2457df4afd28ab9c5da9ccf0f487ac497e66398d362edde8d767ce5d78a5ac6c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:51.880884Z digest=sha256:e39fecaadd428bae734044fd6a9c775081fea95645e8b8d38bb93afcd8deebfc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.028049Z digest=sha256:4fa4bf0cf01aa7ccf2b80a960a6a0029531ebe98975a1deb24b4f5e783577ad9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.114298Z digest=sha256:f534a3bc7aa8daa64ea1dced6e8e398fff9131235f42f725b553e1711b814450

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.328876Z digest=sha256:fb92de08c8318de23cd3bcb220f8bb186c906accc8611b357e9a65068efe1b80

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.428524Z digest=sha256:b06c807590ac40bdd624255d4ffe02b8875e1edd88d07e42f73eeec61d808f0d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.516630Z digest=sha256:329cfdc10f47af9f967a5b4a6604ad291a6974ff4c01d1274756d871b5c98110

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.612000Z digest=sha256:2e02dabce90142c35a420dd7eea57e7f33aa434ca8ee2ef720a5215d15a12e12

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.726287Z digest=sha256:272d720be316b54d0b6b4f8bda4987b2377bd808708967deee69f0f6cee6bff8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.810324Z digest=sha256:a2a8b03d47fc1cb3e01679f5da587fef62c235653d9137a17f5dd3e15264a8a1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.872662Z digest=sha256:32ed438a1b6b09e2bd1baf0dc9920023ff0b5b9770f1f4d1a6d8833abd1e113b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:53.017977Z digest=sha256:61213dc84c57aa6f2ec73fac35051af3a8fbe6e1895f34237354ecc5a8e8fdc6

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:52:52.215801Z digest=sha256:813fd260ea2ffd2798c581b7ce926b89df3a4c5684530412ea1b325b27ea5484

Pith citing papers

No inbound Pith citation observations are available.