Aug 2026· PLoS ONE· Vol 21, pp. e0357202· 0 citations· 35 references
Medicine
TL;DR
Particle Dynamics-based Routing is introduced, a novel routing framework inspired by the controllable trajectories of particles in physical force fields that can maintain constant packet header size independent of network scale, while supporting trajectory-based routing with reduced forwarding overhead at intermediate nodes.
Abstract
Scalable and resource-efficient packet routing remains a fundamental challenge in modern communication networks, particularly in emerging Internet-of-Things and sensor network deployments where node capabilities are severely constrained. Existing routing paradigms, which includes source routing, hop-by-hop table-driven forwarding and other state-of-the-art frameworks, face inherent scalability limitations arising from either increasing packet header overhead or growing routing table complexity. This paper introduces Particle Dynamics-based Routing (PDR), a novel routing framework inspired by the controllable trajectories of particles in physical force fields. In PDR, network topology is abstracted as a discretized spatial field in which packets are routed along physics-driven trajectories determined by initial launch parameters and pre-assigned logical force distributions at nodes. This enables forwarding decisions at intermediate nodes without reliance on destination-specific routing tables or path-encoded headers. A gravitational-field realization of the framework is presented to demonstrate how routing complexity can be shifted from core network nodes to edge-based pre-launch computation processes. Through theoretical formulation and simulation-based evaluation, the study shows that PDR can maintain constant packet header size independent of network scale, while supporting trajectory-based routing with reduced forwarding overhead at intermediate nodes. The framework further enables natural privacy semantics by limiting exposure of destination information during packet traversal. These characteristics position PDR as a scalable routing alternative for large-scale and resource-constrained network environments. Beyond its immediate applicability, the proposed paradigm establishes a new trajectory-centric perspective on routing design, which opens opportunities for future extensions involving multi-field routing strategies, hierarchical trajectory composition, and routing in higher-dimensional network abstractions.
Semantic Potential Field Routing (SPFR), a distributed IoA routing algorithm that integrates executor discovery and reselection into hop-by-hop forwarding, is introduced and proves loop freedom and finite-hop termination and derive an explicit additive error bound under bounded visibility relative to the full-visibilit...
Ye-Guang Qin, Liang-Qi Peng, Feng-Xiao Tang et al.· 0 citations
For distributed link-state deployments on stable inclined-shell topologies, these results show that area division is a principled, geometry-driven design choice; they do not claim that PBAR supersedes centralized or geographic routing.
Sirapop Theeranantachai, Manda Tran, Liz Izhikevich et al.· 0 citations
The effectiveness of SyOpt for minimizing link congestion for routings perfectly resilient for up to one link failure is demonstrated and its potential for continuous application in online monitoring and timely routing optimization, under dynamically fluctuating traffic demands is discussed.
Csaba Györgyi, Kim G. Larsen, Stefan Schmid et al.· 0 citations
MSQ-RPL leverages a reward-propagation mechanism inspired by Q-learning to dynamically guide forwarding decisions, combining adaptive scoring with lightweight control dissemination to enhance scalability and local responsiveness.
M. Alilou, Amin Babazadeh Sangar, K. Majidzadeh et al.· Cluster Computing· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.