A hybrid energy harvesting framework for energy efficiency in wireless sensor networks based smart grid applications

Yildiz, Hüseyin Uğur; Güngör, Vehbi Çağrı; Tavlı, Bülent

doi:10.23919/medhocnet.2018.8407079

Cited by 23 publications

(16 citation statements)

References 14 publications

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“…The DCPVP protocol has enhanced the network performances compared to classical clustered approaches. Some approaches are based on renewable energy to save energy in wireless sensor networks [8,9]. However, renewable resources are unstable and unsuitable for critical applications where making a decision requires low delay.…”

Section: Related Workmentioning

confidence: 99%

Efficient Routing Approach Using a Collaborative Strategy

Aziz

Aznaoui

2020

Journal of Sensors

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Wireless sensor networks (WSNs) are a huge number of sensors, which are distributed in area monitoring to collect important signals. WSNs are widely used in several applications such as home automation, environment, and healthcare monitoring. However, most of these applications face various difficulties due to sensor design. Therefore, the major challenge of designing WSNs is saving the energy consumed during communication and extending the network lifetime. Multicriteria Decision Analysis (MCDA) methods have been exploited for saving network energy. However, the majority of researches focus on the Cluster Head (CH) selection. In this paper, we aim to enhance the process of forwarder selection using an efficient combined multicriteria model. The proposed scheme improved the intercluster communication by controlling the distance separating CHs from the sink node. To minimize the cluster density, this work consists of activating only sensor nodes that detect enough strong signals. The activation phase presents a fault-tolerant technique to succeed in the communication process. Moreover, the proposed work is aimed at selecting the most efficient hops, which are responsible for routing data to the sink using the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. Simulation results proved that our new protocol maximized the residual energy by 15% and 25% and the network lifetime by 35% and 47% compared to the Distributed Clustering Protocol using Voting and Priority (DCPVP) and Low-Energy Adaptive Clustering Hierarchy (LEACH), respectively.

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Section: Related Workmentioning

confidence: 99%

Efficient Routing Approach Using a Collaborative Strategy

Aziz

Aznaoui

2020

Journal of Sensors

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“…This paper adopts the multi-path fading energy consumption model under different channel modes proposed in [19,20]. The energy loss of data transmission is given below:…”

Section: Cluster Communicationmentioning

confidence: 99%

Multi‐path unequal clustering protocol based on ant colony algorithm in wireless sensor networks

Wang

Tong

2020

IET Networks

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For the requirement of low power consumption in wireless sensor networks, from the point of view of prolonging the life cycle of the whole network and improving the utilisation rate of the network, this study proposes a LEACH-EA protocol based on LEACH algorithm. In order to increase the probability of being elected as a cluster head node so that more nodes in the network can share the transmission energy equally, the residual energy factor and the influence factor of node distance are added to the cluster head election threshold. Considering the energy loss of single-hop transmission and the limitation of singlehop transmission on the maximum transmission distance of equipment, the ant colony algorithm is used to find the optimal transmission path for nodes iteratively. Finally, by comparing with LEACH, MODLEACH, LEACH-GA, simulation experiments show that LEACH-EA protocol has significantly improved in network life cycle, total network data transmission and cluster head number. The network utilisation rate of LEACH-EA is 431.3, 135.7 and 38.6% higher than the other three algorithms, respectively.

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“…Many protocols have made some improvements to LEACH [16,17,18,19], mostly focusing on clustering, cluster head election, routing and other issues, such as Hybrid Energy-Efficient Distributed Clustering, (HEED) protocol [20]. Some studies use renewable energy to replenish energy in wireless sensor networks [21,22]. However, renewable energy sources are unstable and unevenly distributed and cannot be used as a reliable power source.…”

Section: Analysis Of Clustering Protocol In Wireless Sensor Networkmentioning

confidence: 99%

A Method for Energy Balance and Data Transmission Optimal Routing in Wireless Sensor Networks

Liu

2019

Sensors

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Wireless sensor networks are widely used in many fields. Nodes in the network are typically powered by batteries. Because the energy consumption of wireless communication is related to the transmission distance, the energy consumption of nodes in different locations is different, resulting in uneven energy distribution of nodes. In some special applications, all nodes are required to work at the same time, and the uneven energy distribution makes the effective working time of the system subject to the node with the largest energy consumption. The commonly used clustering protocol can play a role in balancing energy consumption, but it does not achieve optimal energy consumption. This paper proposes to use the power supply line to connect the nodes to fully balance the energy. The connection scheme with the shortest power line length is also proposed. On the basis of energy balance, the method of transmitting data with the best hop count is proposed, which fully reduces the power consumption of the data transmission. The simulation results show that the proposed method can effectively reduce the energy consumption and prolong the lifetime of wireless sensor networks.

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A hybrid energy harvesting framework for energy efficiency in wireless sensor networks based smart grid applications

Cited by 23 publications

References 14 publications

Efficient Routing Approach Using a Collaborative Strategy

Efficient Routing Approach Using a Collaborative Strategy

Multi‐path unequal clustering protocol based on ant colony algorithm in wireless sensor networks

A Method for Energy Balance and Data Transmission Optimal Routing in Wireless Sensor Networks

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