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DUAL-BLADE: Dual-Path NVMe-Direct KV-Cache Offloading for Edge LLM Inference Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models Efficient, VRAM-Constrained xLM Inference on Clients Folding Tensor and Sequence Parallelism for Memory-Efficient Transformer Training & Inference DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Serving RaMP: Runtime-Aware Megakernel Polymorphism for Mixture-of-Experts Spark Policy Toolkit: Semantic Contracts and Scalable Execution for Policy Learning in Spark Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directions PolyKV: A Shared Asymmetrically-Compressed KV Cache Pool for Multi-Agent LLM Inference A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations ITAS: A Multi-Agent Architecture for LLM-Based Intelligent Tutoring Latency and Cost of Multi-Agent Intelligent Tutoring at Scale TACO: Efficient Communication Compression of Intermediate Tensors for Scalable Tensor-Parallel LLM Training FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost CommFuse: Hiding Tail Latency via Communication Decomposition and Fusion for Distributed LLM Training A Taxonomy and Resolution Strategy for Client-Level Disagreements in Federated Learning Usable Agent Discovery for Decentralized AI Systems Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioning Promoting Simple Agents: Ensemble Methods for Event-Log Prediction GraphLeap: Decoupling Graph Construction and Convolution for Vision GNN Acceleration on FPGA AGNT2: Autonomous Agent Economies on Interaction-Optimized Layer 2 Infrastructure FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels Stream-CQSA: Avoiding Out-of-Memory in Attention Computation via Flexible Workload Scheduling A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing Federated Learning over Blockchain-Enabled Cloud Infrastructure Optimal Routing for Federated Learning over Dynamic Satellite Networks: Tractable or Not? Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers
Blockchain as an IoT intermediary
M. Sipek, M. Zagar, B. Mihaljevic · 2021-12-16 · via cs.DC updates on arXiv.org

Blockchain technology provides a private, secure, transparent decentralized exchange of data. Also, blockchain is not limited to a particular area, but it has a wide range of applications and can be integrated into a variety of Internet interactive systems. For example, the Internet of Things (IoT), supply chain tracking, Electronic Health Records (EHR), digital forensics, identity management, trustless payments, and other key business elements will all benefit from its implementation. Next layer solutions such as Ethereum 2.0, Polkadot, Cardano, and other Web 3.0 technologies provide developers versatility. Moreover, these platforms utilize smart contracts which are similar to standard, traditionalized software during development but offer key utilities to end-users such as online wallets, secure data with transparent rules. Blockchain is receiving a lot of attention in educational technology (EduTech) as it aims to achieve a more transparent and multipurpose educational system. In addition to smart contract technology which defines how data should be registered, gathered and processed, blockchain can be used as an IoT intermediary for mobile usage. Therefore, we implemented an educational learning platform powered by blockchain technology to examine feasibility in industry and academic environment. In essence, this is a web application which is adapted to mobile platform and connected to blockchain for crucial data exchanges. In this paper we want to emphasize the potential of blockchain technology in multiple sectors as well as the need to really understand the underlying principles which are allowing disruptability of traditional centralized software solutions.