Tootfinder

Visualizing Cloud-native Applications with KubeDiagrams
Philippe Merle, Fabio Petrillo
https://arxiv.org/abs/2505.22879 https://arxiv…

Visualizing Cloud-native Applications with KubeDiagrams
Modern distributed applications increasingly rely on cloud-native platforms to abstract the complexity of deployment and scalability. As the de facto orchestration standard, Kubernetes enables this abstraction, but its declarative configuration model makes the architectural understanding difficult. Developers, operators, and architects struggle to form accurate mental models from raw manifests, Helm charts, or cluster state descriptions. We introduce KubeDiagrams, an open-source tool that trans…

This https://arxiv.org/abs/2505.16508 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Edge-First Language Model Inference: Models, Metrics, and Tradeoffs
The widespread adoption of Language Models (LMs) across industries is driving interest in deploying these services across the computing continuum, from the cloud to the network edge. This shift aims to reduce costs, lower latency, and improve reliability and privacy. Small Language Models (SLMs), enabled by advances in model compression, are central to this shift, offering a path to on-device inference on resource-constrained edge platforms. This work examines the interplay between edge and clo…

Studentenvisum für die #USA ? Geh' zur Botschaft und bring' Dein digitales Leben mit: "Under the screening process, consular officers would examine applicants’ posts, shares, and comments across platforms such as Instagram, X, and TikTok for content they deem to be threatening to national security, ..."

Check out and share my latest blog post, “Hijacked Minds and Broken Trust”
https://www.speedofcreativity.org/2025/06/19/hijacked-minds-and-broken-trust/
(btw I blogged this on my iPad, which I’m trying to use more for media creation and sharing)

Leveraging Large Language Model for Intelligent Log Processing and Autonomous Debugging in Cloud AI Platforms
Cheng Ji, Huaiying Luo
https://arxiv.org/abs/2506.17900

Leveraging Large Language Model for Intelligent Log Processing and Autonomous Debugging in Cloud AI Platforms
With the increasing complexity and rapid expansion of the scale of AI systems in cloud platforms, the log data generated during system operation is massive, unstructured, and semantically ambiguous, which brings great challenges to fault location and system self-repair. In order to solve this problem, this paper proposes an intelligent log processing and automatic debugging framework based on Large Language Model (LLM), named Intelligent Debugger (LLM-ID). This method is extended on the basis o…

Optimal Auction Design for Dynamic Stochastic Environments: Myerson Meets Naor
Yeon-Koo Che, Andrew B. Choi
https://arxiv.org/abs/2505.22862 https://

Optimal Auction Design for Dynamic Stochastic Environments: Myerson Meets Naor
Allocation of goods and services often involves both stochastic supply and stochastic demand. Motivated by applications such as cloud computing, gig platforms, and blockchain auctions, we study the design of optimal selling mechanisms in an environment where buyers with private valuations arrive stochastically and are assigned goods that also arrive stochastically, and either buyers or goods can be held in a queue at costs until allocation. The optimal mechanism dynamically leverages competitiv…

Big Data Energy Systems: A Survey of Practices and Associated Challenges
Lunodzo J. Mwinuka, Massimo Cafaro, Lucas Pereira, Hugo Morais
https://arxiv.org/abs/2507.19154 https://…

Big Data Energy Systems: A Survey of Practices and Associated Challenges
Energy systems generate vast amounts of data in extremely short time intervals, creating challenges for efficient data management. Traditional data management methods often struggle with scalability and accessibility, limiting their usefulness. More advanced solutions, such as NoSQL databases and cloud-based platforms, have been adopted to address these issues. Still, even these advanced solutions can encounter bottlenecks, which can impact the efficiency of data storage, retrieval, and analysi…

Meta Battles an ‘Epidemic of Scams’ as Criminals Flood Instagram and Facebook (WSJ, 15 May 2025)
https://www.wsj.com/tech/meta-fraud-facebook-instagram-813363c8
Paywall free version:

Jio Platforms debuts JioPC, a cloud PC service offered via its set-top box; Counterpoint: 70% of Indian households have a TV, but only 15% of them own a PC (Jagmeet Singh/TechCrunch)
https://techcrunch.com/2025/07/11/indias-richest-man-wants-to-turn-eve…

India's richest man wants to turn every TV into a PC | TechCrunch
Jio Platforms, the digital arm of Reliance Industries, has launched a virtual desktop service called JioPC for televisions.

Rethinking the confidential cloud through a unified low-level abstraction for composable isolation
Adrien Ghosn, Charly Castes, Neelu S. Kalani, Yuchen Qian, Marios Kogias, Edouard Bugnion
https://arxiv.org/abs/2507.12364

Rethinking the confidential cloud through a unified low-level abstraction for composable isolation
Securing sensitive cloud workloads requires composing confidential virtual machines (CVMs) with nested enclaves or sandboxes. Unfortunately, each new isolation boundary adds ad-hoc access control mechanisms, hardware extensions, and trusted software. This escalating complexity bloats the TCB, complicates end-to-end attestation, and leads to fragmentation across platforms and cloud service providers (CSPs). We introduce a unified isolation model that delegates enforceable, composable, and atte…

Slides for today's #MediaEdLab #MediaEdClub webinar on "Privacy, Power and Platforms"
htt…

Privacy, Power, and Platforms - MediaEd Club (7 July 2025) by wesfryer.com
Privacy, Power, and Platforms 7 July 2025 Facilitated by Wes Fryer mediaeducationlab.com/mediaed-club/upcoming-meetings

Action Alert from @… : Tell Congress: Don't Outlaw Encrypted Applications
https://act.eff.org/action/tell-congress-don-t-outlaw-encrypted…

Tell Congress: Don't Outlaw Encrypted Applications
It shouldn't be against the law to provide an encrypted app. But if the STOP CSAM Act passes, it would make it a crime to offer encryption, because it could "facilitate" the sharing of illegal child abuse material (CSAM)—even if there's no evidence that a platform or service intended to do so. The law would undermine digital security for all internet users, impacting private messaging and email app providers, social media platforms, cloud storage providers, and many other internet intermediar…

Did you miss today’s #MediaEdClub webinar, “Privacy, Power, and Platforms?” Check out the archived / recorded video and all related links:
https://mediaeducationlab.com/events/pri…

Supporting Intel(r) SGX on Multi-Package Platforms
Simon Johnson, Raghunandan Makaram, Amy Santoni, Vinnie Scarlata
https://arxiv.org/abs/2507.08190 https:…

Supporting Intel(r) SGX on Multi-Package Platforms
Intel(r) Software Guard Extensions (SGX) was originally released on client platforms and later extended to single socket server platforms. As developers have become familiar with the capabilities of the technology, the applicability of this capability in the cloud has been tested. Various Cloud Service Providers (CSPs) are demonstrating the value of using SGX based Trusted Execution Environments (TEE) to create a new paradigm of Confidential Cloud Computing. This paper describes the additional …

Please join me for today’s (July 7) free #MediaEdLab webinar, “Privacy, Power, and Platforms”
https://mediaeducationlab.com/events/privacy-power-and-platforms
We w…

Semantic Communication-Enabled Cloud-Edge-End-collaborative Metaverse Services Architecure
Yuxuan Li, Sheng Jinag, Bizhu Wang
https://arxiv.org/abs/2506.10001

Semantic Communication-Enabled Cloud-Edge-End-collaborative Metaverse Services Architecure
With technology advancing and the pursuit of new audiovisual experiences strengthening, the metaverse has gained surging enthusiasm. However, it faces practical hurdles as substantial data like high-resolution virtual scenes must be transmitted between cloud platforms and VR devices. Specifically, the VR device's wireless transmission hampered by insufficient bandwidth, causes speed and delay problems. Meanwhile, poor channel quality leads to data errors and worsens user experience. To solve th…

[PODCAST] The problem(s) with platforms by #DemocracyWorks with #CoryDoctorow
https://pca.st/episode/026e66ba…

Robot Context Protocol (RCP): A Runtime-Agnostic Interface for Agent-Aware Robot Control
Lambert Lee, Joshua Lau
https://arxiv.org/abs/2506.11650 https://

Robot Context Protocol (RCP): A Runtime-Agnostic Interface for Agent-Aware Robot Control
The Robot Context Protocol (RCP) is a lightweight, middleware-agnostic communication protocol designed to simplify the complexity of robotic systems and enable seamless interaction between robots, users, and autonomous agents. RCP provides a unified and semantically meaningful interface that decouples client-facing operations from backend implementations, supporting a wide range of deployment environments including physical robots, cloud-based orchestrators, and simulated platforms. Built on HT…

Please join me on July 7th for next month's MediaEd Club webinar for the Media Education Lab: "Privacy, Power, and Platforms"
https://mediaeducationlab.com/index.php/events/privacy-power-and-platforms
If you missed today's / this month…

ARRC: Explainable, Workflow-Integrated Recommender for Sustainable Resource Optimization Across the Edge-Cloud Continuum
Brian-Frederik Jahnke, Ren\'e Brinkhege, Jan Peter Meyer, Daniel Tebernum, Falk Howar
https://arxiv.org/abs/2507.12032

ARRC: Explainable, Workflow-Integrated Recommender for Sustainable Resource Optimization Across the Edge-Cloud Continuum
Achieving sustainable, explainable, and maintainable automation for resource optimization is a core challenge across the edge-cloud continuum. Persistent overprovisioning and operational complexity often stem from heterogeneous platforms and layered abstractions, while systems lacking explainability and maintainability become fragile, impede safe recovery, and accumulate technical debt. Existing solutions are frequently reactive, limited to single abstraction layers, or require intrusive platfo…

Sustainability Flags for the Identification of Sustainability Posts in Q&A Platforms
Sahar Ahmadisakha, Lech Bialek, Mohamed Soliman, Vasilios Andrikopoulos
https://arxiv.org/abs/2507.02695

Sustainability Flags for the Identification of Sustainability Posts in Q&A Platforms
In recent years, sustainability in software systems has gained significant attention, especially with the rise of cloud computing and the shift towards cloud-based architectures. This shift has intensified the need to identify sustainability in architectural discussions to take informed architectural decisions. One source to see these decisions is in online Q&A forums among practitioners' discussions. However, recognizing sustainability concepts within software practitioners' discussions remain…

(1/3) Please join me today on Zoom at 12pm ET / 11am CT / 10am MT / 9am PT for "Beyond the Algorithmic Feed," a free MediaEd Club webinar for the Media Education Lab:
https://mediaeducationlab.com/index.php/events/beyond-algorithmic-feed
While som…

RLHGNN: Reinforcement Learning-driven Heterogeneous Graph Neural Network for Next Activity Prediction in Business Processes
Jiaxing Wang, Yifeng Yu, Jiahan Song, Bin Cao, Jing Fan, Ji Zhang
https://arxiv.org/abs/2507.02690

RLHGNN: Reinforcement Learning-driven Heterogeneous Graph Neural Network for Next Activity Prediction in Business Processes
Next activity prediction represents a fundamental challenge for optimizing business processes in service-oriented architectures such as microservices environments, distributed enterprise systems, and cloud-native platforms, which enables proactive resource allocation and dynamic service composition. Despite the prevalence of sequence-based methods, these approaches fail to capture non-sequential relationships that arise from parallel executions and conditional dependencies. Even though graph-ba…

This https://arxiv.org/abs/2505.22862 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Optimal Auction Design for Dynamic Stochastic Environments: Myerson Meets Naor
Allocation of goods and services often involves both stochastic supply and stochastic demand. Motivated by applications such as cloud computing, gig platforms, and blockchain auctions, we study the design of optimal selling mechanisms in an environment where buyers with private valuations arrive stochastically and are assigned goods that also arrive stochastically, and either buyers or goods can be held in a queue at costs until allocation. The optimal mechanism dynamically leverages competitiv…

This https://arxiv.org/abs/2502.00722 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
Recent advancements in Large Language Models (LLMs) have led to increasingly diverse requests, accompanied with varying resource (compute and memory) demands to serve them. However, this in turn degrades the cost-efficiency of LLM serving as common practices primarily rely on homogeneous GPU resources. In response to this problem, this work conducts a thorough study about serving LLMs over heterogeneous GPU resources on cloud platforms. The rationale is that different GPU types exhibit distinct…

Big Data-Driven Fraud Detection Using Machine Learning and Real-Time Stream Processing
Chen Liu, Hengyu Tang, Zhixiao Yang, Ke Zhou, Sangwhan Cha
https://arxiv.org/abs/2506.02008 …

Big Data-Driven Fraud Detection Using Machine Learning and Real-Time Stream Processing
In the age of digital finance, detecting fraudulent transactions and money laundering is critical for financial institutions. This paper presents a scalable and efficient solution using Big Data tools and machine learning models. We utilize realtime data streaming platforms like Apache Kafka and Flink, distributed processing frameworks such as Apache Spark, and cloud storage services AWS S3 and RDS. A synthetic dataset representing real-world Anti-Money Laundering (AML) challenges is employed t…

Distributed Intelligence in the Computing Continuum with Active Inference
Victor Casamayor Pujol, Boris Sedlak, Tommaso Salvatori, Karl Friston, Schahram Dustdar
https://arxiv.org/abs/2505.24618

Distributed Intelligence in the Computing Continuum with Active Inference
The Computing Continuum (CC) is an emerging Internet-based computing paradigm that spans from local Internet of Things sensors and constrained edge devices to large-scale cloud data centers. Its goal is to orchestrate a vast array of diverse and distributed computing resources to support the next generation of Internet-based applications. However, the distributed, heterogeneous, and dynamic nature of CC platforms demands distributed intelligence for adaptive and resilient service management. Th…

Performance Measurements in the AI-Centric Computing Continuum Systems
Praveen Kumar Donta, Qiyang Zhang, Schahram Dustdar
https://arxiv.org/abs/2506.22884

Performance Measurements in the AI-Centric Computing Continuum Systems
Over the Eight decades, computing paradigms have shifted from large, centralized systems to compact, distributed architectures, leading to the rise of the Distributed Computing Continuum (DCC). In this model, multiple layers such as cloud, edge, Internet of Things (IoT), and mobile platforms work together to support a wide range of applications. Recently, the emergence of Generative AI and large language models has further intensified the demand for computational resources across this continuum…