Speaker
Description
Nuclear facilities are gradually deploying large-scale wireless sensing systems to construct nuclear monitoring networks for continuous monitoring of equipment conditions and environmental parameters, such as Monitoring System of EAST's Nuclear Radiation. In such networks, sensing data is frequently queried and reused under dynamic wireless conditions, which places stringent requirements on data availability and delivery efficiency. Named Data Networking (NDN), with its data-centric communication paradigm and in-network caching, enables repeated data access through cache reuse and mitigates single-point failures caused by unstable links or node outages. However, when monitoring queries exhibit strong correlation and network conditions change frequently, existing NDN mechanisms suffer from inefficient cache utilization and redundant Interest transmissions. To address these challenges, this paper proposes an association-aware network-coded NDN (NC-NDN) framework with a distributed caching strategy tailored for nuclear sensing environments. By incorporating random linear network coding, data retrieval is shifted from packet-level access to content delivery based on linear network coding, enabling efficient multipath parallel transmission without relying on a single data source. Without altering the fundamental NDN communication paradigm, each node maintains a lightweight cache trail to capture historical request patterns and identify highly correlated coded blocks, enabling coordinated cache organization and adaptive in-network re-encoding. Experimental results demonstrate that the proposed framework achieves consistently lower data retrieval latency and hop count than representative baseline schemes, confirming its effectiveness in improving data delivery efficiency.
| Minioral | Yes |
|---|---|
| IEEE Member | No |
| Are you a student? | Yes |