Real-time RSS-based positioning system using neural network algorithm

Abkari, Safae El; Mhamdi, Jamal El; Abkari, El Hassan El

doi:10.11591/ijeecs.v22.i3.pp1601-1610

Cited by 3 publications

(4 citation statements)

References 22 publications

(23 reference statements)

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“…The delay is defined as the time between the receiver node received the packets and the sender node forward the packet. It is measured by the (7). From this figure, while the node density raises, the node delay also increases in the network.…”

Section: Average Delaymentioning

confidence: 97%

“…Hence, in WSN, the plan of an energy-efficient routing technique is the significant point [6]. Generally, the localization techniques are separated into two parts such as evaluation of distance applying angle of arrival, residual signal strength indication, and time of arrival, [7]. Position computation by triangulation as well as trilateration [8].…”

Section: Introductionmentioning

confidence: 99%

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Fusion of cuckoo search and hill climbing techniques based optimal forwarder selection and detect the intrusion

Madhuri

Mungara

2022

IJEECS

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The cuckoo search (CS) technique is applying to discover the optimal route from source to destination. The main objective of this work is to offer suitable solutions for getting better the optimal routing and communicating the data via reliable sensor nodes. This CS optimization method not capable for managing the diversity of the solutions. To solve this issue, we use the CS technique to hybridize it with the hill climbing (HC) technique to minimize the probability of early convergence. This approach introduces a fusion of CS and HC techniques (CSHC) based optimal forwarder selection and detect the Intrusion in wireless sensor network (WSN) . Here, a Bayesian thresholding method is predict the received signal strength and link reliability parameter for identifying intrusion in the network. The hill - climbing technique is able to attain the best solutions in a smaller period than other local search techniques. In CSHC, the optimal forwarderis selection by fitness function. This fitness function is computed based on sensor node lifetime, sensor link reliability, and buffer availability. In this app roach, the experimental results suggest that the CSHC for improving 35% throughput and minimizes the 23.52% packet lossescompared to the baseline approaches.

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Section: Average Delaymentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Fusion of cuckoo search and hill climbing techniques based optimal forwarder selection and detect the intrusion

Madhuri

Mungara

2022

IJEECS

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“…An enhanced ant colony optimization method for solving the packet drop issue. This approach contains an update of local and global pheromone to improve path examination and manipulation [17]. Traffic aggregation and multihopping WSN approach can create a great load.…”

Section: Related Workmentioning

confidence: 99%

Reinforcement Learning to Improve QoS and Minimizing Delay in IoT

Subramaniam¹,

Vedanarayanan²,

Mubarakali³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Machine Learning concepts have raised executions in all knowledge domains, including the Internet of Thing (IoT) and several business domains. Quality of Service (QoS) has become an important problem in IoT surrounding since there is a vast explosion of connecting sensors, information and usage. Sensor data gathering is an efficient solution to collect information from spatially disseminated IoT nodes. Reinforcement Learning Mechanism to improve the QoS (RLMQ) and use a Mobile Sink (MS) to minimize the delay in the wireless IoT s proposed in this paper. Here, we use machine learning concepts like Reinforcement Learning (RL) to improve the QoS and energy efficiency in the Wireless Sensor Network (WSN). The MS collects the data from the Cluster Head (CH), and the RL incentive values select CH. The incentives value is computed by the QoS parameters such as minimum energy utilization, minimum bandwidth utilization, minimum hop count, and minimum time delay. The MS is used to collect the data from CH, thus minimizing the network delay. The sleep and awake scheduling is used for minimizing the CH dead in the WSN. This work is simulated, and the results show that the RLMQ scheme performs better than the baseline protocol. Results prove that RLMQ increased the residual energy, throughput and minimized the network delay in the WSN.

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“…Link quality is expressed through link quality evaluation. Although unstable [27], this strategy. The localization methods are typically divided into two categories, such as the distance using angle of arrival, residual signal strength indication (RSSI), and time of arrival [28].…”

mentioning

confidence: 98%

Fuzzy based clustering and improved ant colony optimization for collecting data via mobile sink in wireless sensor networks

Gurunathan,

Sakthivel,

Datchanamoorthy

2023

IJEECS

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<span>Energy efficient routing of data from sensor to base station (BS) is attained utilizing the clustering of sensor nodes, thus minimizing the number of hops and circling the task of the cluster head (CH) sporadically. In addition, the clusters near to the BS take a substantial load over multi-hop communication. The hot spot problem affects wireless sensor networks (WSNs) with BS nodes, which is caused by sensor nodes close to the BS allowing for increased traffic load. So, the entire network lifespan is minimized owing to the element some nodes drain their energy resources much faster equated to the break. To solve these issues fuzzy based clustering and form the optimal route (FCOR) by mobile sink (MS) approach for efficient data collection is proposed. The fuzzy logic method is used for elected the CH by node remaining energy, node connectivity and node distance parameters. Discovering an optimal movable trajectory for the MS is serious so as to attain energy efficiency. Improved ant colony optimization (IACO) method is a better solution to discovering an optimal traversal route. Simulation results proves that FCOR increases the energy efficiency, throughput and minimized the network delay in the WSN.</span>

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Real-time RSS-based positioning system using neural network algorithm

Cited by 3 publications

References 22 publications

Fusion of cuckoo search and hill climbing techniques based optimal forwarder selection and detect the intrusion

Fusion of cuckoo search and hill climbing techniques based optimal forwarder selection and detect the intrusion

Reinforcement Learning to Improve QoS and Minimizing Delay in IoT

Fuzzy based clustering and improved ant colony optimization for collecting data via mobile sink in wireless sensor networks

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