Void Hole Avoidance Based on Sink Mobility and Adaptive Two Hop Vector-Based Forwarding in Underwater Wireless Sensor Networks

Rehman, Zia Ur; Iqbal, Arshad; Yang, Bailin; Hussain, Takasar

doi:10.1007/s11277-021-08518-9

Cited by 12 publications

(7 citation statements)

References 26 publications

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“…(1) selection (yes), (2) next stage (routing), and (3) rejection state. The process is depicted in the following figure (2).…”

Section: Proposed Systemmentioning

confidence: 99%

“…UWSNs are essential for exploring and investigating underwater environments. UWSNs can provide useful information from an area, which is more than 70.00 percent of the Earth's surface covered by water [1,2]. The UWSN is composed of a large number of Autonomous Underwater Vehicles (AUVs) that are used to collect data from deployed sensor nodes [3].…”

Section: Introductionmentioning

confidence: 99%

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CEER: Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

Shah¹,

Hussain²,

Shah³

et al. 2023

CSSE

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Underwater acoustic sensor networks (UWASNs) aim to find varied offshore ocean monitoring and exploration applications. In most of these applications, the network is composed of several sensor nodes deployed at different depths in the water. Sensor nodes located at depth on the seafloor cannot invariably communicate with nodes close to the surface level; these nodes need multihop communication facilitated by a suitable routing scheme. In this research work, a Cluster-based Cooperative Energy Efficient Routing (CEER) mechanism for UWSNs is proposed to overcome the shortcomings of the Co-UWSN and LEACH mechanisms. The optimal role of clustering and cooperation provides load balancing and improves the network profoundly. The simulation results using MATLAB show better performance of CEER routing protocol in terms of various parameters as compared to Co-UWSN routing protocol, i.e., the average end-to-end delay of CEER was 17.39, Co-UWSN was 55.819 and LEACH was 70.08. In addition, the average total energy consumption of CEER was 9.273, and LEACH was 45.33. The packet delivery ratio of CEER was 53.955, CO-UWSN was 42.047, and LEACH was 30.31. The stability period CEER was 130.9, CO-UWSN was 129.3, and LEACH was 119.1. The obtained results maximized the lifetime and improved the overall performance of the CEER routing protocol.

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“…(1) selection (yes), (2) next stage (routing), and (3) rejection state. The process is depicted in the following figure (2).…”

Section: Proposed Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

CEER: Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

Shah¹,

Hussain²,

Shah³

et al. 2023

CSSE

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show abstract

“…Also taken into consideration and proposed for WSN are three distinct scenarios with the numbers WSN-(1), WSN-( 2), and WSN- (3). There are now different sensor node ranges and numbers for each WSN; for example, WSN-(1) had 100 sensor nodes, WSN-(2) had 100 (hundred) sensor nodes, and WSN-(3) had the same amount of sensor nodes as WSN-(1) and WSN- (2). The amount of CH selections varies between these scenarios, which is the fundamental distinction.…”

Section: The Proposed Modelmentioning

confidence: 99%

Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

Ahmad,

Hussain,

Shah

et al. 2024

CMC

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Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and cost. One of them is a sensor network with embedded sensors working as the primary nodes, termed Wireless Sensor Networks (WSNs), in which numerous sensors are connected to at least one Base Station (BS). These sensors gather information from the environment and transmit it to a BS or gathering location. WSNs have several challenges, including throughput, energy usage, and network lifetime concerns. Different strategies have been applied to get over these restrictions. Clustering may, therefore, be thought of as the best way to solve such issues. Consequently, it is crucial to analyze effective Cluster Head (CH) selection to maximize efficiency throughput, extend the network lifetime, and minimize energy consumption. This paper proposed an Accelerated Particle Swarm Optimization (APSO) algorithm based on the Low Energy Adaptive Clustering Hierarchy (LEACH), Neighboring Based Energy Efficient Routing (NBEER), Cooperative Energy Efficient Routing (CEER), and Cooperative Relay Neighboring Based Energy Efficient Routing (CR-NBEER) techniques. With the help of APSO in the implementation of the WSN, the main methodology of this article has taken place. The simulation findings in this study demonstrated that the suggested approach uses less energy, with respective energy consumption ranges of 0.1441 to 0.013 for 5 CH, 1.003 to 0.0521 for 10 CH, and 0.1734 to 0.0911 for 15 CH. The sending packets ratio was also raised for all three CH selection scenarios, increasing from 659 to 1730. The number of dead nodes likewise dropped for the given combination, falling between 71 and 66. The network lifetime was deemed to have risen based on the results found. A hybrid with a few valuable parameters can further improve the suggested APSO-based protocol. Similar to underwater, WSN can make use of the proposed protocol. The overall results have been evaluated and compared with the existing approaches of sensor networks.

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“…The delay consists of the transmission delay, the propagation delay of the signal, the processing delay of the data, and the queuing delay in the entire network. From sender to destination, when a signal travels and carries data, which undergoes these mentioned delays, is counted as the end-to-end delay of the network [8,23].…”

Section: End To End Delaymentioning

confidence: 99%

DLSA: Delay and Link Stability Aware Routing Protocol for Flying Ad-hoc Networks (FANETs)

Hussain

Faisal³

et al. 2021

Wireless Pers Commun

Self Cite

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Flying Ad-hoc Network (FANET) is a new class of Mobile Ad-hoc Network in which the nodes move in three-dimensional (3-D) ways in the air simultaneously. These nodes are known as Unmanned Aerial Vehicles (UAVs) that are operated live remotely or by the predefined mechanism which involves no human personnel. Due to the high mobility of nodes and dynamic topology, link stability is a research challenge in FANET. From this viewpoint, recent research has focused on link stability with the highest threshold value by maximizing Packet Delivery Ratio and minimizing End-to-End Delay. In this paper, a hybrid scheme named Delay and Link Stability Aware (DLSA) routing scheme has been proposed with the contrast of Distributed Priority Tree-based Routing and Link Stability Estimationbased Routing FANET's existing routing schemes. Unlike existing schemes, the proposed scheme possesses the features of collaborative data forwarding and link stability. The simulation results have shown the improved performance of the proposed DLSA routing protocol in contrast to the selected existing ones DPTR and LEPR in terms of E2ED, PDR, Network Lifetime, and Transmission Loss. The Average E2ED in milliseconds of DLSA was measured 0.457 while DPTR was 1.492 and LEPR was 1.006. Similarly, the Average PDR in %age of DLSA measured 3.106 while DPTR was 2.303 and LEPR was 0.682. The average Network Lifetime of DLSA measured 62.141 while DPTR was 23.026 and LEPR was 27.298. At finally, the Average Transmission Loss in dBm of DLSA measured 0.975 while DPTR was 1.053 and LEPR was 1.227.

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Void Hole Avoidance Based on Sink Mobility and Adaptive Two Hop Vector-Based Forwarding in Underwater Wireless Sensor Networks

Cited by 12 publications

References 26 publications

CEER: Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

CEER: Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

DLSA: Delay and Link Stability Aware Routing Protocol for Flying Ad-hoc Networks (FANETs)

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