Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-08T01:21:12.701500Z
Paper Citation Record · LEDGER
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum
As of 2 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2604.24507.
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 2026-08-01T06:32:01.292127+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
40 of 40 outbound references displayed
- verified exact0
- verified fuzzy40
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bd3d0bd3-6d55-4728-9fa5-040fe41c78bf · outbound
This paper cites The computing continuum: From iot to the cloud.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum The computing continuum: From iot to the cloud
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.755043Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 510d98eb-37e7-42e2-998e-07e618ddec7e · outbound
This paper cites Placing Computational Tasks Within Edge-Cloud Continuum: A DRL Delay Minimization Scheme.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Placing Computational Tasks Within Edge-Cloud Continuum: A DRL Delay Minimization Scheme
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.773695Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation a2e8042f-5d3b-4970-b7ad-10a15e68cbb1 · outbound
This paper cites Emerging edge computing technologies for distributed iot systems.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Emerging edge computing technologies for distributed iot systems
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.787907Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation b05f687d-e203-4bbc-af14-ade657603f22 · outbound
This paper cites Learning anticipatory decision for distributed systems with robustness guarantees.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Learning anticipatory decision for distributed systems with robustness guarantees
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.751901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 4a8b72de-60f7-4fd1-80fe-db51a8cfa878 · outbound
This paper cites Exploring the potential of distributed computing continuum systems.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Exploring the potential of distributed computing continuum systems
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.762527Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 5830f183-c0c2-4d78-8ff6-03b45e6451fc · outbound
This paper cites HOODIE: Hybrid computation offloading via distributed deep reinforcement learning in delay-aware cloud-edge continuum.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum HOODIE: Hybrid computation offloading via distributed deep reinforcement learning in delay-aware cloud-edge continuum
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.766041Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation f7fc0904-aa5f-49e4-92f4-5b3a08490ee8 · outbound
This paper cites A review on computational intelligence techniques in cloud and edge computing.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum A review on computational intelligence techniques in cloud and edge computing
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.780749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation aecb3a22-0416-43b5-8738-da7cf1fa31fd · outbound
This paper cites Dynamic service placement for mobile micro-clouds with predicted future costs.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Dynamic service placement for mobile micro-clouds with predicted future costs
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.769947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation c95911b9-a004-46af-a9c2-754bee91af63 · outbound
This paper cites Deadline-constrained multi-resource task mapping and allocation for edge-cloud sys- tems.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Deadline-constrained multi-resource task mapping and allocation for edge-cloud sys- tems
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.715081Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation b7a07c38-6954-4f4a-9ed0-2c93fb064de9 · outbound
This paper cites Adaptive ai-enhanced computation offloading with machine learning for qoe optimization and energy-efficient mobile edge systems.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Adaptive ai-enhanced computation offloading with machine learning for qoe optimization and energy-efficient mobile edge systems
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.738299Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 49cef64d-75f3-4e4e-a692-43ed9b409b33 · outbound
This paper cites Computation offloading in resource-constrained multi-access edge computing.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Computation offloading in resource-constrained multi-access edge computing
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.707139Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 967ef160-e08e-4c25-9270-d6095524e70e · outbound
This paper cites PDPPnet: Prioritized Delay-aware and Peer-to- Peer Task Offloading in Cloud-Edge Continuum with Double Dueling Deep Q-Networks.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum PDPPnet: Prioritized Delay-aware and Peer-to- Peer Task Offloading in Cloud-Edge Continuum with Double Dueling Deep Q-Networks
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.758600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 565ad922-963f-4147-adf7-b6db62d6ac2a · outbound
This paper cites Resource scheduling in edge computing: A survey.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Resource scheduling in edge computing: A survey
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.711306Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation d2b26b1f-be2c-4b40-9570-f685f08d743f · outbound
This paper cites Joint management of compute and radio resources in mobile edge computing: A market equilibrium approach.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Joint management of compute and radio resources in mobile edge computing: A market equilibrium approach
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.741538Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 1890ad81-66aa-4059-85cc-910d269fb48a · outbound
This paper cites An efficient distributed task offloading scheme for vehicular edge computing networks.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum An efficient distributed task offloading scheme for vehicular edge computing networks
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.777174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 90631d8b-856d-4c6b-8401-1fbdcc59dc90 · outbound
This paper cites Dependent task offloading for edge computing based on deep reinforcement learning.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Dependent task offloading for edge computing based on deep reinforcement learning
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.792007Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 1cfdaca0-eef7-49e4-a998-b0dfa0366f05 · outbound
This paper cites Prioritization based task offloading in UA V-assisted edge networks.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Prioritization based task offloading in UA V-assisted edge networks
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.839930Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 009c2fc8-5bc9-4e66-953b-9c9b0ef89035 · outbound
This paper cites Deep reinforcement learning for task offloading in mobile edge computing systems.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Deep reinforcement learning for task offloading in mobile edge computing systems
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.813035Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 43abdf11-8a93-4591-874a-8f7d39a2ce58 · outbound
This paper cites Deep reinforcement learning techniques for dynamic task of- floading in the 5g edge-cloud continuum.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Deep reinforcement learning techniques for dynamic task of- floading in the 5g edge-cloud continuum
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.748545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 4a821027-56d1-4613-867f-892009cc1ef5 · outbound
This paper cites Edge intelli- gence for energy-efficient computation offloading and resource allocation in 5g beyond.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Edge intelli- gence for energy-efficient computation offloading and resource allocation in 5g beyond
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.851428Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation ff9c9339-e80b-4b50-b083-1ab0fd7d7e0f · outbound
This paper cites Beyond the edge: An advanced exploration of reinforcement learning for mobile edge computing, its applications, and future research trajectories.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Beyond the edge: An advanced exploration of reinforcement learning for mobile edge computing, its applications, and future research trajectories
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.847123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation fbc30b0d-ec66-4673-b2cd-bed3b2220706 · outbound
This paper cites Multi-objective offloading optimization in mec and vehicular- fog systems: A distributed-td3 approach.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Multi-objective offloading optimization in mec and vehicular- fog systems: A distributed-td3 approach
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.728258Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 51b546d2-98a5-4ccb-b5ad-9ef8922a0d3c · outbound
This paper cites Deepedge: A deep reinforcement learning based task orchestrator for edge computing.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Deepedge: A deep reinforcement learning based task orchestrator for edge computing
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.836036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation b44ca7cf-ec60-4a23-9164-b00882655aed · outbound
This paper cites COOLER: Cooperative Computation Offloading in Edge- Cloud Continuum Under Latency Constraints via Multi-Agent Deep Reinforcement Learning.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum COOLER: Cooperative Computation Offloading in Edge- Cloud Continuum Under Latency Constraints via Multi-Agent Deep Reinforcement Learning
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.843277Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation fd61b7ec-d39d-45eb-9fe5-d612a75dab6c · outbound
This paper cites Bottleneck identification in cloudified mobile networks based on distributed telemetry.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Bottleneck identification in cloudified mobile networks based on distributed telemetry
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.721904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 1a7b1d7b-6cb0-4445-b9ca-f427ce595bc0 · outbound
This paper cites Towards a lightweight distributed telemetry for microservices.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Towards a lightweight distributed telemetry for microservices
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.718708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation b97b3fdc-0174-4736-8132-f44ec46506fd · outbound
This paper cites Delay-optimal computation task scheduling for mobile-edge computing sys- tems.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Delay-optimal computation task scheduling for mobile-edge computing sys- tems
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.725100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 00c80e22-63af-4e27-be94-f6a236fc4385 · outbound
This paper cites Statistical analysis of the generalized processor sharing scheduling discipline.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Statistical analysis of the generalized processor sharing scheduling discipline
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.731644Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 32db7245-d8c5-4d9c-8b0c-5b1a4a076b06 · outbound
This paper cites Toffee: Task offloading and frequency scaling for energy efficiency of mobile devices in mobile edge computing.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Toffee: Task offloading and frequency scaling for energy efficiency of mobile devices in mobile edge computing
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.744943Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 9aee03ea-af5c-481e-83a0-c997a1594de4 · outbound
This paper cites Online management for edge-cloud collaborative continuous learning: A two-timescale approach.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Online management for edge-cloud collaborative continuous learning: A two-timescale approach
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.735063Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 8c4de93e-9dd5-461a-8409-b8fc759fafb9 · outbound
This paper cites Multi-agent drl-based task offloading in multiple ris-aided iov networks.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Multi-agent drl-based task offloading in multiple ris-aided iov networks
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.784236Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation f20738f1-a2ad-4570-908a-09b1c443198c · outbound
This paper cites Deep reinforcement learning: From q-learning to deep q-learning.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Deep reinforcement learning: From q-learning to deep q-learning
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.820779Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation c333cbea-b0f7-4d19-b62a-24aaefef08af · outbound
This paper cites The bellman equation for minimizing the maximum cost.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum The bellman equation for minimizing the maximum cost
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.816880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 0e4e1417-a5c4-4635-b9ee-00c668c9bba7 · outbound
This paper cites Experience replay for continual learning.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Experience replay for continual learning
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.824514Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation fff796f1-0047-40d6-b9ee-b669e60c8a3e · outbound
This paper cites Double deep q- learning-based path selection and service placement for latency- sensitive beyond 5g applications.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Double deep q- learning-based path selection and service placement for latency- sensitive beyond 5g applications
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.809338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 6f06a9e4-3c73-4b65-83e3-c5a7b5b504c3 · outbound
This paper cites Completely fair scheduler.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Completely fair scheduler
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.805476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 9f0cc286-667c-4b45-ac3c-b7139e88df8f · outbound
This paper cites Com- putation offloading and resource allocation in wireless cellular networks with mobile edge computing.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Com- putation offloading and resource allocation in wireless cellular networks with mobile edge computing
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.828524Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation a35767fb-28c8-4acc-a846-e8ab7473f0c8 · outbound
This paper cites Enhanced round-robin algorithm in the cloud computing environment for optimal task scheduling.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Enhanced round-robin algorithm in the cloud computing environment for optimal task scheduling
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.832391Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 6b75b06a-a158-4d3b-bf8b-b36924c55456 · outbound
This paper cites Offloading schemes in mobile edge computing for ultra-reliable low latency communications.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Offloading schemes in mobile edge computing for ultra-reliable low latency communications
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.796428Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Observation 1184741f-9b1f-4057-94f7-b68b270a398e · outbound
This paper cites Development of Methods for obtaining DC and low frequency AC magnetic cleanliness in space missions.
DECOFFEE: Decentralized Reinforcement Learning for Time-critical Workload Offloading and Energy Efficiency across the Computing Continuum Development of Methods for obtaining DC and low frequency AC magnetic cleanliness in space missions
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T00:28:18.802192Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.
Pith citing papers
No inbound Pith citation observations are available.