Optimized Location Dependent Data Retrieval Approach For Internet Of Things Based On Named Data Networking

Ali, Aboodi Ahed Hussein (2025) Optimized Location Dependent Data Retrieval Approach For Internet Of Things Based On Named Data Networking. PhD thesis, Perpustakaan Hamzah Sendut.

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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.

Item Type:	Thesis (PhD)
Subjects:	Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Pusat Pengajian Sains Komputer (School of Computer Sciences) > Thesis
Depositing User:	Mr Hasmizar Mansor
Date Deposited:	27 Apr 2026 02:10
Last Modified:	27 Apr 2026 02:10
URI:	http://eprints.usm.my/id/eprint/63986

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