Low Power Enhanced Leach Protocol to Extend WSN Lifespan

Karimullah, Shaik; Vishnuvardhan, D.; Riyazuddin, K.; Kanakam, Prathyusha; Sonia, K.

doi:10.1007/978-981-15-7961-5_51

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…This method uses a random probability function to pick cluster-head nodes. ( [16] and [17] attempt to enhance the LEACH method. In [18], each node is allocated a rank depending on the route's cost and the number of connections between nodes, and CHs are selected based on this rank.…”

Section: Related Workmentioning

confidence: 99%

An Intelligent SDN-Based Clustering Approach for Optimizing IoT Power Consumption in Smart Homes

Nazari

Tavassolian

Abbasi

et al. 2022

Wireless Communications and Mobile Computing

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As a novel technology, the Internet of Things (IoT) has many applications in diverse fields, especially in smart homes. IoT includes a variety of communication networks and technologies which facilitate communication between heterogeneous devices. One of the primary challenges of IoT is energy consumption. This paper introduces a new Software Defined Network-based (SDN-based) clustering approach using intelligent algorithms for energy conservation in IoT. The proposed method uses an evolutionary algorithm to identify the required number of clusters and ensures their distribution in the environment. A virtual network is also employed to ensure network coverage and the formation of balanced clusters. Clustering, steady, and routing are the main steps of the proposed method that the clustering step is done in SDN. By expanding the steady phase and leveraging energy-based greedy routing, the network’s lifetime increases. After simulation in MATLAB, the proposed method is tested then the results are compared with other well-known algorithms. The evaluation results indicate that the proposed method has improved in terms of metrics such as energy consumption and network lifetime. The proposed approach improves energy consumption by 31%, 28%, 8% and 21% than FPA, MCFL, BEEG and NodeRanked respectively. The lifetime has been improved by 34% and 71% than BEEG and NodeRanked, respectively, and more than 100% for MCFL and FPA.

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Section: Related Workmentioning

confidence: 99%

An Intelligent SDN-Based Clustering Approach for Optimizing IoT Power Consumption in Smart Homes

Nazari

Tavassolian

Abbasi

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

“…The mobile sink follows the data collection path, which seems more efficient than the existing proposals on many parameters. [14][15][16] This section discusses the various factors that motivate the selection of this project for our dissertation. Firstly, IoT is swiftly and steadily becoming a major part of our lives, be it in the development of smart cities, smart home appliances, vehicles, environmental monitoring to control issues of global warming, and pollution, and in disaster management.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Data Aggregation and Density-Based Spatial Clustering of Applications with Noise for Activity Monitoring in Wireless Sensor Networks

Singh¹,

din²

2022

Eng. Sci.

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Clustering saves energy and extends network longevity in applications such as activity monitoring in wireless sensor networks. Clustering separate tes nodes into clusters from which the cluster head can collect and send data to the base station. The current investigation also demonstrates data aggregation at the cluster head before sending it to the base station. The cluster head is chosen based on leftover energy and distance from the sink and other network nodes. The current study found that the existing clustering protocol decays its energy quickly, but our proposal can overcome these challenges and sensors can survive longer. This paper proposes Density-based Spatial Clustering of Applications with Noise (DB-SCAN) clustering algorithms to make data gathering and transmitting of data energy efficient. The data aggregation protocol will collect the packets and combine them. Further, it will be forwarded using the clustering approach. It is used to improve transmission efficiency by reducing the transmission of redundant data to the sink. This proposed protocol, Energy Efficient Cluster based Data Aggregation (EECDA), will help increase network lifetime by ensuring uniform distribution of energy amongst the nodes.

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“…Besides, wireless sensor nodes provide their required energy from low-power batteries without replacing or recharging possibilities. WSNs are usually employed in harsh and disaster environments for a long time [26,27]. In other words, limitation on the battery is another main challenge on wireless networks that influences their lifetime [28,29].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Routing Mechanism on Homogenous Wireless Sensor Networks using Genetic Algorithm

Danehchin

2021

Preprint

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Data collection on Wireless Sensor Networks (WSNs) is a significant challenge to satisfy the requirements of various applications. Providing an energy-efficient routing technique is the primary step in data collection over WSNs. The existing data collection techniques in the WSNs field struggle with the imbalance load distribution and the short lifetime of the network. This paper proposes a novel mechanism to select cluster-heads, cluster the wireless sensor nodes, and determine the optimal route from source nodes to the sink. We employ the genetic algorithm to solve the routing problem considering the hop-count of the cluster-heads to the sink, the number of each cluster member, residual energy of cluster-heads, and the number of cluster-heads connected to the sink as the fitness criteria. Our proposed mechanism uses a greedy approach to calculate the hop-count of each cluster-head to the sink for integrating the clustering and routing process on WSNs. The simulation results demonstrate that our proposed mechanism improves the energy consumption, the number of live nodes, and the lifetime of the network compared to other data collection approaches on WSNs.

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Low Power Enhanced Leach Protocol to Extend WSN Lifespan

Cited by 5 publications

References 9 publications

An Intelligent SDN-Based Clustering Approach for Optimizing IoT Power Consumption in Smart Homes

An Intelligent SDN-Based Clustering Approach for Optimizing IoT Power Consumption in Smart Homes

Energy Efficient Data Aggregation and Density-Based Spatial Clustering of Applications with Noise for Activity Monitoring in Wireless Sensor Networks

An Integrated Routing Mechanism on Homogenous Wireless Sensor Networks using Genetic Algorithm

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