Improved Genetic Algorithm Based Energy Efficient Routing in Two-Tiered Wireless Sensor Networks

Zain-ul-Abidin, Muhammad; Muhammad, .; Maqsood, Hammad; Qasim, Umar; Khan, Zahoor Ali; Javaid, Nadeem

doi:10.1109/nbis.2016.81

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…Factors like distance and time are taken into consideration when evaluating cluster head node health as part of Ref. [4] and FGSA [5] . The Fuzzy dependent Secured Authentication and Clustering (FSAC) Algorithm evaluates the various types of data packets transferred inside the sensors to avoid an attack.…”

Section: Related Workmentioning

confidence: 99%

Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

Meenakshi,

Ahmad,

Prabu

et al. 2024

Tsinghua Sci. Technol.

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The Wireless Sensor Network (WSN) is a network that is constructed in regions that are inaccessible to human beings. The widespread deployment of wireless micro sensors will make it possible to conduct accurate environmental monitoring for a use in both civil and military environments. They make use of these data to monitor and keep track of the physical data of the surrounding environment in order to ensure the sustainability of the area. The data have to be picked up by the sensor, and then sent to the sink node where they may be processed. The nodes of the WSNs are powered by batteries, therefore they eventually run out of power. This energy restriction has an effect on the network life span and environmental sustainability. The objective of this study is to further improve the Engroove Leach (EL) protocol's energy efficiency so that the network can operate for a very long time while consuming the least amount of energy. The lifespan of WSNs is being extended often using clustering and routing strategies. The Meta Inspired Hawks Fragment Optimization (MIHFO) system, which is based on passive clustering, is used in this study to do clustering. The cluster head is chosen based on the nodes' residual energy, distance to neighbors, distance to base station, node degree, and node centrality. Based on distance, residual energy, and node degree, an algorithm known as Heuristic Wing Antfly Optimization (HWAFO) selects the optimum path between the cluster head and Base Station (BS).They examine the number of nodes that are active, their energy consumption, and the number of data packets that the BS receives. The overall experimentation is carried out under the MATLAB environment. From the analysis, it has been discovered that the suggested approach yields noticeably superior outcomes in terms of throughput, packet delivery and drop ratio, and average energy consumption.

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Section: Related Workmentioning

confidence: 99%

Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

Meenakshi,

Ahmad,

Prabu

et al. 2024

Tsinghua Sci. Technol.

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“…Sureshkumar and Sabena 15 analyze the numerous forms of data packets exchanged inside the sensors to prevent the attack by using the fuzzy-dependent secured authentication and clustering (FSAC) Algorithm. For such energy usage, 16 FSAC is applied to use the qualified routing route. 17 This approach identifies the next transmission node to enhance the effective data packet route set-up by utilizing the fuzzy logic framework, 18 the network wireless sensor frame (E2SDRSNF) consisting of three elements.…”

Section: Review Of Literaturementioning

confidence: 99%

Energy‐efficient routing protocol and optimized passive clustering in WSN for SMART grid applications

Vinodha¹,

Durairaj

Padmavathi³

2021

Int J Communication

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Due to low cost, ease of implementation and flexibility of wireless sensor networks (WSNs), WSNs are considered to be an essential technology to support the smart grid (SG) application. The prime concern is to increase the lifetime in order to find the active sensor node and thereby to find once the sensor node (SN) dies in any region. For this reason, an energy-efficient Dynamic Source Routing (DSR) protocol needs to provide the right stability region with a prolonged network lifetime. This work is an effort to extend the network's existence by finding and correcting the considerable energy leveraging behaviors of WSN. We build a comprehensive model based on real measures of SG path loss for different conditions by using the characteristics of WSN nodes and channel characteristics. This method also establishes a hierarchical network structure of balanced clusters and an energy-harvesting SN. The cluster heads (CHs) are chosen by these SN using a low overhead passive clustering strategy. The cluster formation method is focused on the use of passive clustering of the particle swarm optimization (PSO). For the sake of eliminating delayed output in the WSN, energy competent dynamic source routing protocol (EC-DSR) is used. Chicken swarm optimization (CSO) in which optimum cluster path calculation shall be done where distance and residual energy should be regarded as limitation. Finally, the results are carried out with regard to the packet distribution ratio, throughput, overhead management, and average end-to-end delay to demonstrate the efficiency of the proposed system.

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“…Improved PSO clustering to minimize the transmission distance therefore obtained the optimum energy consumption, however minimizing the overall energy consumption and balancing energy consumption among nodes throughout the network lifetime. Zain-ul-Abidin et al 8 proposed an algorithm LEACH for homogenous network to enhance the network lifetime, less energy consumption, and more stability of network. Cluster head selection considers the remaining energy of sensor nodes in the network.…”

Section: Related Workmentioning

confidence: 99%

Multiple input and multiple output and energy‐aware peering routing protocol for energy consumption in sensor networks

Raj

Chinnadurai

2019

Int J Communication

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Wireless sensor network consumes large number of energy-constrained nodes that are used to monitor the external devices while transferring the information in the sensor networks. At the time of the information transmission process, node contains high energy, and battery of node may be recharged continuously, which leads to reduction of the entire information transmission system performance. This paper introduces the multiple input and multiple output (MIMO) method with energy-efficient protocol for reducing the energy consumption in the network. Initially, the network coverage is determined by applying the shadow fading sensing model, and the clusters are formed with the help of the particle dual clustering process. After the cluster is formed, the information has been transmitted with the help of the energyaware peering routing protocol (EPR), which reduces the network traffic and also improves the energy efficiency with efficient manner. Then, the efficiency of the system is analyzed with the help of experimental results in terms of coverage fraction, accuracy of the cluster, and energy consumption.KEYWORDS multiple input and multiple output (MIMO) method with energy-efficient protocol, particle dual clustering process, shade fading sensing model, the energy-aware peering routing protocol (EPR), wireless sensor network

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Improved Genetic Algorithm Based Energy Efficient Routing in Two-Tiered Wireless Sensor Networks

Cited by 6 publications

References 15 publications

Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

Energy‐efficient routing protocol and optimized passive clustering in WSN for SMART grid applications

Multiple input and multiple output and energy‐aware peering routing protocol for energy consumption in sensor networks

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