Routing Technology in Wireless Sensor Network Based on Ant Colony Optimization Algorithm

Zheng, Enxing; Liu, Ranran

doi:10.1007/s11277-016-3755-1

Cited by 12 publications

(5 citation statements)

References 6 publications

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“…Figure 1 is a transit map of VRP. VRP transport of goods refers to the goods required for distribution, and in the process of distribution and transportation, attributes and transport objects are consistent (Zheng, et al 2016) [10]. Due to the diversity of the vehicle, there will be a certain difference in the delivery requirements during the transportation and distribution of the goods.…”

Section: " 21 a Review Of Mathematical Models For Multimodal Transpor...mentioning

confidence: 99%

The Construction and Optimization of Finished Vehicle Logistics Multimodal Transportation Routing Problem Model based on Ant Colony Algorithm under the Background of Belt and Road Initiative

Wang

2023

Preprint

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Vehicle logistics is a very important mode of freight car combination logistics. In China, more than 80% of the total logistics operation through highway transportation is based on the completion of vehicle logistics. Because of the lack of transportation mode in the whole vehicle logistics process, the problems of the relatively small batch of transportation but large duplicate batches are very common. Therefore, in the aspect of cost control, the whole vehicle logistics system of our country has much room for improvement compared with western countries. Multimodal transportation can be adopted to reduce costs, and multimodal transport mode of vehicle logistics can also be carried out to avoid the logistics defects caused by single highway transportation, so as to facilitate management and reduce costs. The case analysis to the B Company in the entire vehicle logistics aspect work was carried out in this paper. Combined with the idea of route optimization, a model of vehicle logistics cost budget based on multimodal transportation was established. The ant colony algorithm was adopted, and the validity of the model and calculation method was verified.

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Section: " 21 a Review Of Mathematical Models For Multimodal Transpor...mentioning

confidence: 99%

The Construction and Optimization of Finished Vehicle Logistics Multimodal Transportation Routing Problem Model based on Ant Colony Algorithm under the Background of Belt and Road Initiative

Wang

2023

Preprint

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“…In a nutshell, the above works proposed multihop intelligent routing methods based on ACO algorithm and concentrated on searching for optimized path for data routing. The most of these protocols 11,[33][34][35][36][37]39,40 are based on flat topology, which is not optimized for data transmission and causes congestion, while the other protocols 13,38,41 are based on hierarchical topology to fix the issues of flat topology. Only the protocols 11,36,41 take into consideration the fault tolerance issue among the other protocols.…”

Section: Aco-based Routing Protocolsmentioning

confidence: 99%

“…The works that can be found in previous studies 13,37,38 attempt to optimize the energy consumption in WSNs. Also, Enxing and Ranran 39 employ ACO for WSNs, and their aim is to optimize some very important metrics such as adaptability, multipath transmission, cost, energy consumption, and network lifespan. This paper 40 proposed an ACO algorithm with specific parameters for data routing in WSNs.…”

Section: Related Workmentioning

confidence: 99%

IACO‐ERP: An improved ACO‐based energy‐efficient routing protocol for fog‐based WSNs

Moussa

Hamidi‐Alaoui

Alaoui

2021

Int J Communication

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Summary Wireless Sensor Networks (WSNs) present numerous constraints, which motivate many researchers and which reside mainly in the fact that their resources are limited in terms of communication, calculations, and energy. In particular, the stress linked to energy is considered as a fundamental problem. Indeed, all the sensor elements need energy to function. Thus, controlling the energy consumption of a node remains a major problem for maximizing the lifetime of the network. The clustering and Ant Colony Optimization (ACO) algorithms have been seen as a good solution to route data while maintaining a better network lifetime. However, the existing state‐of‐the‐art cluster and ACO‐based routing protocols perform re‐clustering and fail to restrict the ant searching scope. This consumes a high amount of energy and makes the convergence speed slow. For these reasons, this paper presents an Improved ACO‐based Energy‐efficient Routing Protocol (IACO‐ERP) to mitigate the hot spot problem by proposing a multiple Fog Nodes (FNs)‐based energy‐efficient network model. IACO‐ERP avoids re‐clustering and rotates the Cluster Head (CH) role based on energy among cluster members without any need for control overhead, and also, it proposes to limit the scope of ant searching for optimal route toward the sink based on some specific parameters such as energy and distance, thus avoiding routing loop, slow convergence speed, and excessive energy consumption. The proposed routing protocol is evaluated against some recent and relevant existing solutions. The simulations results reveal that IACO‐ERP provides significant improvement in comparison to its counterparts in terms of various main metrics.

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“…Then, it continuously iterates until the optimal solution of the function is found. For example, the cat swarm algorithm [18], fish migration optimization algorithm [19], ant colony optimization algorithm [20], and genetic algorithm [21] are used to select CHs and find routing paths in a clustering and routing protocol. The calculation results of most meta-heuristic algorithms are random due to the initial parameter settings, and there is a risk of falling into a local optimum when dealing with complex problems.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient, Cluster-Based Routing Protocol for Wireless Sensor Networks Using Fuzzy Logic and Quantum Annealing Algorithm

Wang,

Liu,

Wang

et al. 2024

Sensors

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The main limitation of wireless sensor networks (WSNs) lies in their reliance on battery power. Therefore, the primary focus of the current research is to determine how to transmit data in a rational and efficient way while simultaneously extending the network’s lifespan. In this paper, a hybrid of a fuzzy logic system and a quantum annealing algorithm-based clustering and routing protocol (FQA) is proposed to improve the stability of the network and minimize energy consumption. The protocol uses a fuzzy inference system (FIS) to select appropriate cluster heads (CHs). In the routing phase, we used the quantum annealing algorithm to select the optimal route from the CHs and the base station (BS). Furthermore, we defined an energy threshold to filter candidate CHs in order to save computation time. Unlike with periodic clustering, we adopted an on-demand re-clustering mechanism to perform global maintenance of the network, thereby effectively reducing the computation and overhead. The FQA was compared with FRNSEER, BOA-ACO, OAFS-IMFO, and FC-RBAT in different scenarios from the perspective of energy consumption, alive nodes, network lifetime, and throughput. According to the simulation results, the FQA outperformed all the other methods in all scenarios.

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Routing Technology in Wireless Sensor Network Based on Ant Colony Optimization Algorithm

Cited by 12 publications

References 6 publications

The Construction and Optimization of Finished Vehicle Logistics Multimodal Transportation Routing Problem Model based on Ant Colony Algorithm under the Background of Belt and Road Initiative

The Construction and Optimization of Finished Vehicle Logistics Multimodal Transportation Routing Problem Model based on Ant Colony Algorithm under the Background of Belt and Road Initiative

IACO‐ERP: An improved ACO‐based energy‐efficient routing protocol for fog‐based WSNs

Energy-Efficient, Cluster-Based Routing Protocol for Wireless Sensor Networks Using Fuzzy Logic and Quantum Annealing Algorithm

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