A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms

Wang, Xun; Wu, Huarui; Miao, Yisheng; Zhu, Haojin

doi:10.3390/electronics11060869

Cited by 12 publications

(8 citation statements)

References 39 publications

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“…For clustering of the HSFZ, we used a combination of the DBSCAN algorithm [ 47 ] and naive Bayes classifier, a density-based subspace clustering algorithm that created arbitrary-shaped clusters and eliminated outliers, as shown in Figure 3 . The naive Bayes classifier [ 48 ] was used for the CH selection based on the CH’s conditional probability. The DBSCAN clustering algorithm was suitable for the discovery of subspace clusters of arbitrary shape with a high efficiency in the network.…”

Section: Sf-partition-based Clustering and Relaying (Sfpcr) Schemementioning

confidence: 99%

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SF-Partition-Based Clustering and Relaying Scheme for Resolving Near–Far Unfairness in IoT Multihop LoRa Networks

Mugerwa

Nam

Choi

et al. 2022

Sensors

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Long range (LoRa) is one of the most successful low-power wide-area networking technologies because it is ideally suited for long-distance, low-bit rate, and low-power communications in the unlicensed sub-GHz spectrum utilized for Internet of things (IoT) networks. The effectiveness of LoRa depends on the link budget (i.e., spreading factor (SF), bandwidth (BW), and transmission power (TX)). Due to the near–far effect, the allocation of a link budget to LoRa devices (LDs) in large coverage regions is unfair between them depending on their distance to the GW. Thus, more transmission opportunities are given to some LDs to the detriment of other LD’s opportunities. Numerous studies have been conducted to address the prevalent near–far fairness problem. Due to the absence of a tractable analytical model for fairness in the LoRa network, however, it is still difficult to solve this problem completely. Thus, we propose an SF-partition-based clustering and relaying (SFPCR) scheme to achieve enormous LD connectivity with fairness in IoT multihop LoRa networks. For the SF partition, the SFPCR scheme determines the suitable partitioning threshold point for bridging packet delivery success probability gaps between SF regions, namely, the lower SF zone (LSFZ) and the higher SF zone (HSFZ). To avoid long-distance transmissions to the GW, the HSFZ constructs a density-based subspace clustering that generates clusters of arbitrary shape for adjacent LDs and selects cluster headers by using a binary score representation. To support reliable data transmissions to the GW by multihop communications, the LSFZ offers a relay LD selection that ideally chooses the best relay LD to extend uplink transmissions from LDs in the HSFZ. Through simulations, we show that the proposed SFPCR scheme exhibits the highest success probability of 65.7%, followed by the FSRC scheme at 44.6%, the mesh scheme at 34.2%, and lastly the cluster-based scheme at 29.4%, and it conserves the energy of LDs compared with the existing schemes.

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Section: Sf-partition-based Clustering and Relaying (Sfpcr) Schemementioning

confidence: 99%

“…Steady-state phase: In this phase, the cluster head selection is performed using a naive Bayes classifier [ 48 ]. The GW plays a crucial role in generating the score value needed to categorize normal LoRa devices as CHs or cluster members.…”

Section: Sf-partition-based Clustering and Relaying (Sfpcr) Schemementioning

confidence: 99%

SF-Partition-Based Clustering and Relaying Scheme for Resolving Near–Far Unfairness in IoT Multihop LoRa Networks

Mugerwa

Nam

Choi

et al. 2022

Sensors

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“…WSNs have a large number of sensor nodes that are connected to a base station. In fact, it is difficult to load and reinstall the sensor nodes in remote places [1].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

Hamza¹,

Hashim²,

Elkamchouchi³

et al. 2023

Computer Systems Science and Engineering

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Wireless Sensor Network (WSN) consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment. Designing the energy-efficient data collection methods in largescale wireless sensor networks is considered to be a difficult area in the research. Sensor node clustering is a popular approach for WSN. Moreover, the sensor nodes are grouped to form clusters in a cluster-based WSN environment. The battery performance of the sensor nodes is likewise constrained. As a result, the energy efficiency of WSNs is critical. In specific, the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station (BS). Therefore, energy efficiency and load balancing are very essential in WSN. In the proposed method, a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques (GW-IPSO-TS) was used. The selection of Cluster Heads (CHs) and routing path of every CH from the base station is enhanced by the proposed method. It provides the best routing path and increases the lifetime and energy efficiency of the network. End-to-end delay and packet loss rate have also been improved. The proposed GW-IPSO-TS method enhances the evaluation of alive nodes, dead nodes, network survival index, convergence rate, and standard deviation of sensor nodes. Compared to the existing algorithms, the proposed method outperforms better and improves the lifetime of the network.

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“…Because of their relatively strong mobility and limited energy, the nodes of construction robots have high requirements for the effectiveness of routing protocols. At present, the design and optimization of routing protocols are mainly divided into four categories [ 3 , 4 , 5 ]: (1) Reducing node energy consumption; (2) Reducing node load; (3) Maintaining link stability; (4) Dynamic maintenance [ 6 , 7 ]. Building a high-reliability, large-bandwidth, and low-latency communication network required for coordinated control and scheduling for construction robot clusters [ 8 , 9 ] expounded the construction and spatial modeling of the ground robot cluster communication network and integrated positioning and communication into the robot network, but ignored the complex secondary, coupling superposition characteristics of the industrial site.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on Routing Algorithm of Construction Robot Cluster Enhanced Ad Hoc Network

Wei

Zhao

Chen

2023

Sensors

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An enhanced self-assembling network routing algorithm is proposed for the problem of weak connectivity of communication networks caused by factors such as movement or environmental interference in the construction and operation, and the maintenance of construction robot clusters. Firstly, the dynamic forwarding probability is calculated based on the contribution of nodes joining routing paths to network connectivity, and the robust connectivity of the network is achieved by introducing the connectivity feedback mechanism; secondly, the influence of link quality evaluation index Q balanced hop count, residual energy, and load on link stability is used to select appropriate neighbors for nodes as the subsequent hop nodes; finally, the dynamic characteristics of nodes are combined with the topology control technology to eliminate low-quality links and optimize the topology by link maintenance time prediction and to set robot node priority. The simulation results show that the proposed algorithm can guarantee a network connectivity rate above 97% under heavy load, reduce the end-to-end delay, and improve the network survival time, providing a theoretical basis for achieving stable and reliable interconnection between building robot nodes.

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A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms

Cited by 12 publications

References 39 publications

SF-Partition-Based Clustering and Relaying Scheme for Resolving Near–Far Unfairness in IoT Multihop LoRa Networks

SF-Partition-Based Clustering and Relaying Scheme for Resolving Near–Far Unfairness in IoT Multihop LoRa Networks

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

Research on Routing Algorithm of Construction Robot Cluster Enhanced Ad Hoc Network

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