---
title: "Middleware (A): papers and universities"
description: "Middleware (ACM/IFIP/USENIX International Middleware Conference) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 103 of its papers from 2024–2026 (55 in 2024, 48 in 2025; 2026 not in OpenAlex yet). By the countries of the authors' institutions, the most papers come from the United States (31), Germany (14) and Canada (12)."
url: https://scholar4ai.com/proceedings/middleware
markdown_url: https://scholar4ai.com/proceedings/middleware.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "Middleware (ACM/IFIP/USENIX International Middleware Conference) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 103 of its papers from 2024–2026 (55 in 2024, 48 in 2025; 2026 not in OpenAlex yet). (as of 2026-11-02)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-02T12:20:52+09:00
window: 2026-10-04 to 2026-11-02
source: OpenAlex (CC0)
---

# Middleware: ACM/IFIP/USENIX International Middleware Conference — papers and institutions, 2024–2026

Papers of Middleware, ACM/IFIP/USENIX International Middleware Conference (CORE rank A; field: Distributed computing and systems software), 2024–2026: per year, the institutions, countries and topics, and the most-cited papers. Ranks are those of the CORE Conference Rankings, edition ICORE2026 (portal.core.edu.au), applied to every year shown. Papers are the works OpenAlex lists for the conference's proceedings, or for the issues of a conference-linked journal that publishes its papers (such as PACMPL, PVLDB or ACM TOG), by publication year; workshops, companion volumes, posters and Findings are left out. A paper counts once for each institution and country among its authors' affiliations as OpenAlex assigns them; papers without affiliations in OpenAlex count for none. For conferences published in book series that OpenAlex files as one source (LNCS, LIPIcs, SIAM and IOS Press proceedings), the papers are found by DOI: those of the volumes with the conference's title in Crossref, or LIPIcs DOIs, which name the conference. Conferences without DOIs (PMLR, USENIX, OpenReview) are listed without counts. A dash (–) for a year means OpenAlex has no papers of the conference for it yet: the proceedings are not published or indexed yet, or the conference did not meet that year (some meet every other year). 2026 counts what OpenAlex had indexed by 2026-11-02.

All conferences: https://scholar4ai.com/proceedings.md

## Key findings

- Middleware (ACM/IFIP/USENIX International Middleware Conference) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 103 of its papers from 2024–2026 (55 in 2024, 48 in 2025; 2026 not in OpenAlex yet).
- By the countries of the authors' institutions, the most papers come from the United States (31), Germany (14) and Canada (12).
- The institutions with the most papers are University of Toronto (6), Virginia Tech (5) and Institut national de recherche en sciences et technologies du numérique (4).
- Its most-cited paper of these years is “FLEdge: Benchmarking Federated Learning Applications in Edge Computing Systems” (2024), with 14 citations.

## Papers per year

*Middleware papers per publication year in OpenAlex (–: not in OpenAlex yet)*

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 55 | 54 |
| 2025 | 48 | 48 |
| 2026 | – | – |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S4306420020](https://openalex.org/S4306420020) | The conference's proceedings |

## Who publishes there

*Institutions with the most Middleware papers, 2024–2026*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [University of Toronto](https://scholar4ai.com/institutions/university-of-toronto.md) | 6 |
| 2 | Virginia Tech | 5 |
| 3 | Institut national de recherche en sciences et technologies du numérique | 4 |
| 4 | IBM (United States) | 4 |
| 5 | [Shanghai Jiao Tong University](https://scholar4ai.com/institutions/shanghai-jiao-tong-university.md) | 4 |
| 6 | Argonne National Laboratory | 3 |
| 7 | [Centre National de la Recherche Scientifique](https://scholar4ai.com/institutions/centre-national-de-la-recherche-scientifique.md) | 3 |
| 8 | Georgia Institute of Technology | 3 |
| 9 | Pennsylvania State University | 3 |
| 10 | University of Oregon | 3 |

*Countries with the most Middleware papers, 2024–2026*

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 31 |
| 2 | Germany | 14 |
| 3 | Canada | 12 |
| 4 | Switzerland | 10 |
| 5 | France | 10 |
| 6 | China | 8 |
| 7 | Belgium | 5 |
| 8 | Netherlands | 5 |
| 9 | United Kingdom | 4 |
| 10 | Greece | 4 |

*Keywords with the most Middleware papers, 2024–2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [federated learning](https://scholar4ai.com/keywords/federated-learning.md) | 11 |
| 2 | serverless computing | 11 |
| 3 | edge computing | 8 |
| 4 | Byzantine fault tolerance | 7 |
| 5 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 7 |
| 6 | function-as-a-service | 6 |
| 7 | middleware | 6 |
| 8 | cloud computing | 5 |
| 9 | trusted execution environments | 5 |
| 10 | WebAssembly | 4 |

## Most-cited papers

*Most-cited Middleware papers of 2024–2026 (citations counted by OpenAlex)*

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 14 | [FLEdge: Benchmarking Federated Learning Applications in Edge Computing Systems](https://doi.org/10.1145/3652892.3700751) | 2024-11-27 | Herbert Woisetschläger, Alexander Erben, Ruben Mayer et al. |
| 2 | 12 | [L3: Latency-aware Load Balancing in Multi-Cluster Service Mesh](https://doi.org/10.1145/3652892.3654793) | 2024-11-27 | Olivier Michaelis, Stefan Schmid, Habib Mostafaei |
| 3 | 12 | [Guardian: Safe GPU Sharing in Multi-Tenant Environments](https://doi.org/10.1145/3652892.3700768) | 2024-11-27 | Manos Pavlidakis, Giorgos Vasiliadis, Stelios Mavridis et al. |
| 4 | 10 | [QuickDrop: Efficient Federated Unlearning via Synthetic Data Generation](https://doi.org/10.1145/3652892.3700764) | 2024-11-27 | Akash Dhasade, Yaohong Ding, Song Guo et al. |
| 5 | 10 | [Deep Optimizer States: Towards Scalable Training of Transformer Models using Interleaved Offloading](https://doi.org/10.1145/3652892.3700781) | 2024-11-27 | Avinash Maurya, Jie Ye, M. Mustafa Rafique et al. |
| 6 | 10 | [vPIM: Processing-in-Memory Virtualization](https://doi.org/10.1145/3652892.3700782) | 2024-11-27 | Dufy Teguia, Jiaxuan Chen, Stella Bitchebe et al. |
| 7 | 9 | [Optimal Resource Efficiency with Fairness in Heterogeneous GPU Clusters](https://doi.org/10.1145/3652892.3654792) | 2024-11-27 | Zizhao Mo, Huanle Xu, Wing Cheong Lau |
| 8 | 8 | [In Serverless, OS Scheduler Choice Costs Money: A Hybrid Scheduling Approach for Cheaper FaaS](https://doi.org/10.1145/3652892.3700757) | 2024-11-27 | Yuxuan Zhao, Weikang Weng, Rob V. van Nieuwpoort et al. |
| 9 | 7 | [XChainWatcher: Identifying Anomalies in Cross-Chain Bridges](https://doi.org/10.1145/3721462.3770781) | 2025-12-08 | André Augusto, Rafael Belchior, Jonas Pfannschmidt et al. |
| 10 | 7 | [Towards Interoperability of APIs - an LLM-based approach](https://doi.org/10.1145/3704440.3704788) | 2024-12-02 | R. C. Lehmann |

## Cite this page

Scholar4AI. (2026). Middleware: ACM/IFIP/USENIX International Middleware Conference — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/middleware

```bibtex
@misc{scholar4ai-proceedings-middleware,
  author = {{Scholar4AI}},
  title = {Middleware: ACM/IFIP/USENIX International Middleware Conference — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/middleware}},
  urldate = {2026-11-02},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).