Multi Cluster Scheduling Patents: Leaders & Filing Trends 2026
Filing growth compares 2021 (1,715 records) with 2024 (1,149) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 160,704 records in scope (CR5), not by the ranked leaders only.
What the multi cluster scheduling patent record shows
Multi cluster scheduling covers the methods, architectures and control logic used to distribute compute tasks across more than one cluster — the core problem behind containers and orchestration once a workload outgrows a single cluster boundary. The dataset in scope spans 160,704 published records filed between 2015 and the current data cut-off, drawing on a search string that captures both explicit multi-cluster scheduling claims and the broader combination of multi, cluster and scheduling terms across specifications.
Filing activity rose through the late 2010s, peaked in 2021, and has since eased — though the two most recent years in any trend chart are understated, since publication lags filing by roughly 18 months. The technology composition leans heavily on general digital data processing and network transmission classes, with AI-based computing and business-process classes present but comparatively thin.
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Filing trends and technology concentration
Three views of the same 160,704-record corpus: how filings moved year over year, how those records classify across IPC subclasses, and where applicants filed for protection.
A 2021 peak followed by an understated decline
Annual filings rose from 1,027 in 2017 to a peak of 1,715 in 2021, then eased to 1,149 by 2024 — a -33% move over that three-year span. 2025 and 2026 figures are still filling in as publications catch up with filing dates, so treat the tail of the chart as incomplete rather than as a genuine drop-off.
Digital data processing and network transmission dominate the classification mix
G06F (electric digital data processing) leads at 5.6% of the 160,704 records in scope, followed by H04L (digital information transmission) at 3.9% and H04W (wireless communication networks) at 3.7%. AI-based computing under G06N accounts for 0.9% and business-process class G06Q for 0.7%, both thin relative to the infrastructure classes — since a record can carry multiple IPC codes, these shares add up to more than the record total by design.
Shares are the percentage of the 160,704 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Containers & Orchestration: Multi Cluster Scheduling Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about containers & orchestration: multi cluster scheduling patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaRepresentative filing and most-cited prior art
Multi-queue multi-cluster task scheduling method and system (US20220269536A1)
Filed by Guangdong University of Petrochemical Technology, this record describes training multiple parallel deep neural networks against a constructed data set, then using a reward function that jointly minimises task delay and energy consumption to route a to-be-scheduled state space through the optimised networks for cluster task assignment.The approach ties scheduling decisions directly to a reinforcement-style reward function rather than static heuristics, which is where later design-around activity tends to concentrate.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US6029195A | System for customized electronic identification of desirable objects | 3,395 |
| 2 | US5758257A | System and method for scheduling broadcast of and access to video programs and other data using customer prof… | 2,666 |
| 3 | US20170006135A1 | Systems, methods, and devices for an enterprise internet-of-things application development platform | 1,906 |
| 4 | US20170235848A1 | System and method for fuzzy concept mapping, voting ontology crowd sourcing, and technology prediction | 1,473 |
| 5 | US7020701B1 | Method for collecting and processing data using internetworked wireless integrated network sensors (WINS) | 1,457 |
| 6 | US20030046396A1 | Systems and methods for managing resource utilization in information management environments | 1,408 |
| 7 | US6088722A | System and method for scheduling broadcast of and access to video programs and other data using customer prof… | 1,396 |
| 8 | US20130097706A1 | Automated behavioral and static analysis using an instrumented sandbox and machine learning classification fo… | 1,278 |
| 9 | US6859831B1 | Method and apparatus for internetworked wireless integrated network sensor (WINS) nodes | 1,178 |
| 10 | US20030125040A1 | Multiple-access multiple-input multiple-output (MIMO) communication system | 1,075 |
Citation counts reflect influence within the searched corpus and skew toward older filings; they are not a measure of current commercial relevance.
Each row carries its publication number; clicking a row searches Eureka by that number.
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Browse MCP servers →What the concentration and composition mean for filing strategy
The ranking and classification data point to a field where a handful of large infrastructure and telecom players hold a disproportionate share of filings, while newer computing paradigms remain lightly claimed.
Filing sits with a small leading group
The top five assignees combined account for 29.4% of all 160,704 records in scope, rising to 37.5% across the top ten. That is a top-heavy field for a new entrant to file into directly on core scheduling claims, though it leaves room to differentiate on adjacent technical branches.
Activity has cooled from its 2021 peak
Filings rose to a peak of 1,715 in 2021 before falling to 1,149 by 2024, a -33% move. The two most recent years are still incomplete due to publication lag, so this should be read as a real plateau after a filing surge rather than a signal that the field is closing.
AI-driven scheduling is thin relative to infrastructure claims
G06F and H04L together cover the bulk of classified activity, but G06N sits at just 0.9% of the 160,704 records in scope. Reward-function and learning-based scheduling approaches, like the representative record here, are still a comparatively small slice of the classified art.
Filing activity concentrates in the US and at the EPO
The United States receives the largest volume of filings at 13,355, ahead of the EPO at 3,231 and WIPO/PCT routes at 2,264. Canada, Australia and the UK trail well behind, which matters when deciding where freedom-to-operate work needs to be deepest.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to containers & orchestration: multi cluster scheduling patent landscape, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| International Business Machines Corporation (IBM) | IBM UNITED KINGDOM LTD INTELLECTUAL PROPERTY DEPARTMENT | 22 |
| International Business Machines Corporation (IBM) | IBM (China) Co., Ltd. | 21 |
| Samsung Electronics Co., Ltd. (Korea) | Korea Advanced Institute of Science and Technology (KAIST) | 18 |
| Qualcomm Incorporated | HOU JILEI | 13 |
| Qualcomm Incorporated | WEI CHAO | 10 |
| Huawei Technologies Co., Ltd. | Huawei Technologies (USA) Co., Ltd. | 10 |
| Intel Corporation | Intel IP Corporation | 9 |
| Qualcomm Incorporated | WANG NENG | 9 |
Co-assignee activity is limited to 10 identified pairs, concentrated around large corporate groups filing jointly across national subsidiaries and with university partners — a sign that most multi cluster scheduling work in this corpus is filed by a single assignee rather than jointly developed.
Turning this landscape into a filing or freedom-to-operate decision
The figures above establish where filing activity concentrates and where it thins out. Turning that into a specific claim strategy or design-around plan requires digging into the actual claim language of the leading records.
Map the white space precisely
AI-based computing and business-process classes are lightly claimed relative to core digital data processing. Confirming whether a specific reward-function or learning-based scheduling approach is genuinely open takes claim-by-claim review, not just a class-level share.
Explore white space in EurekaCheck what a leading filer's claims actually block
A large assignee's share of records tells you concentration, not scope. Reading the independent claims of the leading families in this corpus shows which specific mechanisms are locked up and which are described but not tightly claimed.
Analyze claims in EurekaWatch the incomplete recent years
2025 and 2026 filings are still publishing. Before concluding the field has cooled, track how the trend fills in as later publications land.
Set up monitoring in EurekaCommon questions about multi cluster scheduling patents
The assignee ranking covers 100 companies drawn from the 160,704 records in scope, and it is top-heavy: the five leading assignees together hold 29.4% of all records, and the top ten hold 37.5%. The leader alone accounts for 17,241 records, well ahead of the fifth-place holder at 6,059 and the tenth-place holder at 1,937. This is not a full list of every filer, just the ranked leaders the dataset returns, so smaller or newer entrants can still hold meaningful individual families outside this ranking.
Filings rose from 1,027 in 2017 to a peak of 1,715 in 2021, then declined to 1,149 by 2024 — a -33% change over that span. That reads as a real plateau after a filing surge around 2020-2021, though it is not a signal of an ending field, since publication typically lags actual filing by around 18 months. The 2025 and 2026 figures in any chart should be treated as incomplete rather than as evidence of continued decline.
General digital data processing (G06F) leads at 5.6% of the 160,704 records in scope, followed by digital information transmission (H04L) at 3.9% and wireless communication networks (H04W) at 3.7%. AI-based computing (G06N) and business-process data processing (G06Q) are present but much thinner, at 0.9% and 0.7% respectively. Because a single record can carry several IPC codes, these percentages add up to more than 100% and should be read individually, not summed.
The classification data points toward AI-based computing (G06N) and business-process classes (G06Q) as comparatively lightly claimed relative to the dominant digital data processing and network transmission classes. The representative record in this corpus, which uses a reward function balancing task delay and energy consumption across trained neural networks, illustrates the kind of learning-based scheduling mechanism that sits in this thinner territory. Confirming true white space still requires reading the specific claims of records in the adjacent classes rather than relying on class-level shares alone.
The United States receiving office accounts for the largest volume at 13,355 filings, followed by the European Patent Office at 3,231 and the WIPO/PCT route at 2,264. Australia, Canada and the United Kingdom see far fewer filings by comparison, each under 400. For freedom-to-operate work, this distribution means US and European coverage needs the deepest review, with PCT filings worth tracking for their eventual national-phase destinations.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.