inter-process communication design

本文提出一种统一的消息模型，用于描述异构串行数据交换协议，并通过工业工具环境实现，支持自动化开发和标准化及弱形式化串行协议的工程应用。

This work addresses the complexity, routing ambiguity, and unreliable shutdown commonly introduced by ad hoc glue code in existing modular distributed systems. To overcome these issues, the paper proposes CNS—a lightweight, local-first hybrid event bus that seamlessly bridges local and distributed publish-subscribe contexts through a unified event model and consistent routing semantics. CNS employs an asynchronous fire-and-forget primary path while supporting request-response extensions on the same topic. It integrates typed event keys, family-based serialization and validation, and NATS-backed distributed transport. Prototype evaluation demonstrates low-latency performance: approximately 30 microseconds for local delivery, 1.26–1.37 milliseconds for purely distributed communication, and 1.64–1.89 milliseconds for hybrid bridging, with validation overhead remaining manageable—making CNS suitable for structured inter-process communication and efficient messaging among resource-constrained nodes.

Transport-layer protocol development is hindered by environmental heterogeneity and the absence of high-level, target-agnostic programming abstractions, impeding automated analysis, formal verification, and programmable transport research. To address this, we propose TINF—the first event-driven, state-aware, high-level programming abstraction specifically designed for transport protocols—achieving full decoupling between protocol logic and execution targets. TINF employs a C-like restricted syntax to express protocol behavior and introduces a target-agnostic instruction set supporting core operations including data reassembly, packet generation, scheduling, and timer management. It features dual backends: DPDK and Linux XDP. Experimental evaluation demonstrates that TINF significantly improves development efficiency, ensures cross-platform semantic consistency, and establishes a unified foundation for formal modeling and automated verification of transport protocols.

Existing transport-layer hardware struggles to flexibly support the evolution of new protocols due to rigid protocol logic or reliance on protocol-specific assumptions. This work proposes PITA, a novel architecture that reconfigures core components—such as scheduling, packet generation, and data reassembly—through a unified event–state–instruction abstraction model, enabling a protocol-agnostic and line-rate programmable transport-layer datapath. By eliminating protocol-specific assumptions, PITA efficiently supports semantically diverse protocols, including TCP and RoCE, on a single FPGA (Alveo U250) while fully preserving their end-to-end behavioral differences. Experimental results demonstrate that the system meets timing constraints at 250 MHz with low hardware overhead and excellent performance.

Software engineers face significant challenges—including difficulty in modeling, lengthy prototyping cycles, and high verification costs—when developing control algorithms for complex dynamic systems such as communication networks. To address these issues, we propose GIPS, the first model-driven engineering framework that tightly integrates graph-structured integer linear programming (ILP) modeling with automated code generation. Using the domain-specific language GIPSL, users declaratively specify constraints and optimization objectives; GIPS then automatically generates functionally complete, executable Java graph-optimization components. This enables end-to-end rapid prototyping—from high-level specifications to runtime deployment. We validate GIPS on a tree-structured peer-to-peer topology control scenario, demonstrating its correctness, efficiency, and scalability. The full implementation—including source code and a ready-to-run virtual machine demonstration environment—is open-sourced, confirming its practical deployability and engineering utility.

Current agent communication protocols generally lack mechanisms for semantic alignment, clarification, and verification, shifting semantic responsibility onto prompts or application logic and thereby causing poor interoperability and high maintenance costs. This work proposes, for the first time, a human-inspired three-layer communication framework—comprising communication, syntactic, and semantic layers—and systematically analyzes 18 mainstream protocols to expose their structural deficiencies in semantic coordination. Through layered modeling, technical debt identification, and scenario mapping, the study not only derives a practical protocol selection guide but also advances agent communication beyond mere message passing toward a new paradigm of shared understanding, laying the foundation for building semantically robust, secure, and interoperable agent ecosystems.

This work addresses the lack of structural constraints against data leakage in existing federated learning protocols, which hinders trustworthy collaboration under heterogeneous privacy requirements. The authors propose a novel federated transmission protocol, FSTP, which uniquely embeds data encapsulation directly into its architectural design. By leveraging Rust’s type system to prevent raw data exposure at compile time, and integrating unlinkable contextual identity isolation, a Blocklace-based partially ordered event log, and an erasable hash chain, FSTP enables tamper-resistant, cross-domain unlinkable, and verifiable collaboration. The protocol supports “prove-without-exposing” federated interactions and has been integrated into Velyzor, a governance platform for high-security institutions. Both the protocol specification and reference implementation are publicly available under the Apache 2.0 license.

The current internet lacks a structural semantic foundation capable of enabling autonomous systems to comprehend intent, context, and consequences, and reliance on cognitive computing alone is insufficient for safety-critical and socio-technical applications. This work proposes the first “syntactic–semantic internet” architecture, elevating “meaning” to a first-class citizen by introducing a parallel semantic stack that operates in concert with the existing syntactic stack. The resulting three-layer structure—comprising semantic communication, a semantic substrate, and an agent network—provides a foundational blueprint for global semantic interoperability. The paper delineates core architectural components, identifies critical industrial gaps, and systematically outlines the key engineering challenges and developmental pathways necessary to achieve explainable alignment, semantic accountability, and intelligible autonomous behavior.

This work addresses the challenge of efficient inter-process communication and serialization of algebraic data in distributed computing environments by proposing and implementing a tunable serialization framework. The framework supports customizable serialization strategies tailored to algebraic data structures and innovatively adapts the mrdi file format for data transmission in distributed settings. By integrating domain-specific serialization mechanisms with the mrdi format, the system substantially enhances communication efficiency and processing performance for algebraic data across distributed systems. This approach provides flexible and high-performance low-level support for applications that rely heavily on structured algebraic representations, offering both adaptability and scalability without compromising on throughput or latency.

This study addresses the severe fragmentation of large language model (LLM) communication protocols in multi-agent systems, which significantly hinders interoperability. The work proposes the first structured taxonomy specifically tailored to LLM agent communication protocols, developed through an empirical-conceptual bidirectional iterative approach. By systematically analyzing nine prominent open-source protocols, the authors derive a five-dimensional classification framework encompassing communication parties, payload structure, interaction state, discovery mechanisms, and pattern flexibility. The analysis identifies recurring architectural patterns—including hybrid payloads, persistent conversation states, and runtime protocol negotiation—revealing commonalities and evolutionary trends across existing protocols. The study further forecasts a trajectory toward federated, layered protocol stacks and highlights critical research gaps, particularly in privacy preservation and policy enforcement, thereby offering theoretical guidance for future protocol design and selection.