Knowledge-Based Systems, Год журнала: 2025, Номер unknown, С. 113552 - 113552
Опубликована: Апрель 1, 2025
Язык: Английский
Knowledge-Based Systems, Год журнала: 2025, Номер unknown, С. 113552 - 113552
Опубликована: Апрель 1, 2025
Язык: Английский
Applied Soft Computing, Год журнала: 2025, Номер unknown, С. 112757 - 112757
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
3Applied Soft Computing, Год журнала: 2025, Номер unknown, С. 113014 - 113014
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0Smart Cities, Год журнала: 2025, Номер 8(2), С. 64 - 64
Опубликована: Апрель 9, 2025
This work presents an innovative, energy-efficient IoT routing protocol that combines advanced data fusion grouping and strategies to effectively tackle the challenges of management in smart cities. Our employs hierarchical Data Fusion Head (DFH), relay DFHs, marine predators algorithm, latter which is a reliable metaheuristic algorithm incorporates fitness function optimizes parameters such as how closely Sensor Nodes (SNs) group (DFG) are gathered together, distance sink node, proximity SNs within group, remaining energy (RE), Average Scale Building Occlusions (ASBO), Primary DFH (PDFH) rotation frequency. A key innovation our approach introduction techniques minimize redundant transmissions enhance quality DFG. By consolidating from multiple using algorithms, reduces volume transmitted information, leading significant savings. supports both direct routing, where fused flow straight multi-hop PDF chosen based on influential cost considers RE, ASBO. Given proposed efficient failure recovery strategies, redundancy management, techniques, it enhances overall system resilience, thereby ensuring high performance even unforeseen circumstances. Thorough simulations comparative analysis reveal protocol’s superior across metrics, namely, network lifespan, consumption, throughput, average delay. When compared most recent relevant protocols, including Particle Swarm Optimization-based clustering (PSO-EEC), linearly decreasing inertia weight PSO (LDIWPSO), Optimized Fuzzy Clustering Algorithm (OFCA), Novel PSO-based Protocol (NPSOP), achieves very promising results. Specifically, extends lifespan by 299% over PSO-EEC, 264% LDIWPSO, 306% OFCA, 249% NPSOP. It also consumption 254% relative 247% against 253% The throughput improvements reach 67% 59% 53% 50% fusing optimizing sets new benchmark for DFG, offering robust solution diverse deployments.
Язык: Английский
Процитировано
0Knowledge-Based Systems, Год журнала: 2025, Номер unknown, С. 113552 - 113552
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
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