National Academy Science Letters, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 5, 2025
Language: Английский
Cluster Computing, Journal Year: 2024, Volume and Issue: 27(10), P. 13643 - 13673
Published: July 2, 2024
Abstract Metaheuristic algorithms have wide applicability, particularly in wireless sensor networks (WSNs), due to their superior skill solving and optimizing many issues different domains. However, WSNs suffer from several issues, such as deployment, localization, sink node placement, energy efficiency, clustering. Unfortunately, these negatively affect the already limited of WSNs; therefore, need employ metaheuristic is inevitable alleviate harm imposed by on lifespan performance network. Some associated regarding are modelled single multi-objective optimization issues. Single-objective one optimal solution, other has multiple desirable solutions that compete, so-called non-dominated solutions. Several strategies based available address various types concerns relating WSN This review reports discusses literature research metaheuristics evaluation criteria, architectures definitions, applications It also proposes definitions for terms some ongoing difficulties linked topics. Furthermore, this outlines open challenge paths, future trends can be applied (single multi-objective) difficulties, well significant efforts necessary improve efficiency.
Language: Английский
Citations
6
International Journal of Communication Systems, Journal Year: 2025, Volume and Issue: 38(7)
Published: March 20, 2025
ABSTRACT Because of technological advances in the Internet Things (IoT), IoT surveillance applications powered by wireless sensor networks (WSN) play an important role spreading dangerous and nonhazardous data. When using such application, devices must connect multihop (Multi‐H) communication, which overloads relay nodes (RNs). This tends to cause hotspot problems becomes a major problem for network lifetime as RNs use their power more extensively. To address this issue, proposed study introduces novel hybrid‐optimized clustering–based routing protocol (HOC‐RP) issues WSN‐enabled IoT. The is distributed into numerous clusters fuzzy K‐medoid clustering model (Fuzz‐KMC). A new hybrid optimization recognized sine cosine–reptile search (SC‐RSO) algorithm employed optimal CH selection resolve WSN. In addition, enhanced gannet (EGOA) used define route effective data transmission. simulation HOC‐RP carried out Matlab platform, performance evaluated different evaluation metrics. As result, has obtained better 44,768 rounds scenario 1 44,721 2 than existing protocols.
Language: Английский
Citations
0
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: April 26, 2025
Abstract In our modern societies, the wireless sensor network (WSN) is categorized as a smart motivated technology that can be utilized in many work environments and activities to enhance daily life. However, several challenging concerns have been assigned WSN. The clustering process main complex concern still an open problem To support efficient process, two crucial requirements must considered, energy management lifetime extension, especially development of large-scale primary objective this article introduce new meta-heuristic algorithm, denoted hybrid gazelle optimization reptile search algorithm (HGORSA), which optimizes cluster head selection WSNs. proposed mathematical models for exploration exploitation phases traditional (GOA) are enhanced by integrating hunting operator, reduction function, predator cumulative effect operators from RSA. These modifications improve balance between diversification intensification processes, effectively addressing key mentioned above. At same time, they also positively impact overall performance evaluation Various simulation scenarios designed evaluate HGORSA different configurations. First, experiment was conducted with 300 nodes (SNs). experimental results then analyzed assess effectiveness under conditions against six state-of-the-art algorithms. Based on outputs, demonstrated superior compared particle swarm optimization, grey Wolf optimizer, sperm chernobyl disaster algorithm. Specifically, achieved percentage improvements terms stability period (37.3%, 49.6%, 46.8%, 55.3%, 19.1%, 34.4%, respectively), consumption (10.8%, 10.5%, 9.6%, 8.6%, 8.3%, 3.5%, (44.5%, 40.8%, 23.8%, 16.8%, 9.3%, 7.2%, number dead (30.3%, 29.7%, 28.9%, 24.3%, 18%, 11.5%, throughput (36.4%, 43.9%, 34.2%, 25%, 20%, 14.4%, respectively). Moreover, supplementary test efficiency dense sparse networks, where SNs set at 50 500. evaluated based five standard aforementioned metrics. Furthermore, robustness validated using statistical measures, including deviation (Std), average (Avg), worst best values, box plots fitness function across 20 independent runs. results, outperformed other comparative meta-heuristics.
Language: Английский
Citations
0
International Journal of Communication Systems, Journal Year: 2025, Volume and Issue: 38(10)
Published: May 12, 2025
ABSTRACT Underwater wireless sensor networks (UWSNs) face challenges like limited bandwidth, high‐energy consumption, and the energy hole problem, where nodes near sinks deplete faster, reducing network performance lifespan. To address these issues, we propose hybrid optimization‐based sink mobility for mitigation in UWSNs (HOSEMU), utilizing a golden jackal optimization (GJO) enhanced remora (ERO) approach, termed GJERO. GJERO combines GJO's global search ERO's local to enhance cluster head (CH) selection, balancing consumption improving convergence. Sink toward energy‐depleted CHs further ensures efficient data collection extended Simulation results MATLAB show that HOSEMU outperforms existing methods, stability by 19.4% over energy‐efficient routing stable reporting algorithm (EERSDRA) 28.7% energy‐conserving (ECERO). These demonstrate HOSEMU's effectiveness addressing UWSN‐specific enhancing performance.
Language: Английский
Citations
0
National Academy Science Letters, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 5, 2025
Language: Английский
Citations
0