Publication: Optimized Location Dependent Data Retrieval Approach For Internet Of Things Based On Named Data Networking
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Date
2025-02
Authors
Ali, Aboodi Ahed Hussein
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Abstract
The internet of things (iot) demands efficient, adaptable, and scalable data retrieval mechanisms to meet the dual requirements of data-oriented and location-dependent host-oriented scenarios. Named data networking (ndn) offers a promising alternative to traditional ip-based architectures by focusing on content rather than host-based communication. However, existing ndn-based solutions face challenges in resource-constrained environments, including limited support for location-dependent data delivery and retrieval, inefficiencies in multicast forwarding, and high transmission overhead. This research introduces e-ndn, an enhanced ndn architecture tailored for wireless resource-constrained iot environments. E-ndn integrates three core modules: (1) the dlh naming scheme and local-first forwarding, which combines hierarchical location-enabled naming with proximity-aware interest suppression and backup forwarding procedures for enhanced reliability; (2) wildcard-based naming and forwarding, which optimizes multicast data retrieval by consolidating interest requests, reducing redundancy, and enabling more proximate location targeting; and (3) the path-selection module, which dynamically optimizes routing based on node proximity and capabilities, while defining and enabling broadcast domain limits to mitigate congestion.
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Internet of things