A Novel HEED Protocol for Wireless Sensor Networks

Priyadarshi, Rahul; Singh, Lucky; Randheer,; Singh, Anurag

doi:10.1109/spin.2018.8474286

Cited by 57 publications

(12 citation statements)

References 12 publications

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“…Wireless multimedia sensor networks have grown in popularity due to the development of WSN. Sensor nodes in WSN sense and gather data from other nodes, process these data, and then transfer the collected data to the base station by the HEED routing protocol [4]. Environmental monitoring, healthcare, industrial automation units, high-performance building control, traffic management object tracking, military surveillance, and other computing platforms all use sensor networks.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Clustering and Routing Algorithm Using Hybrid Fuzzy with Grey Wolf Optimization in Wireless Sensor Networks

Singh

Deepika²,

Din

et al. 2022

Security and Communication Networks

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Wireless networking is popular due to the “3 any” concept: anyone, anytime, anywhere. Wireless communication technology advancements have covered the opportunities for sustainable development of low-power, low-cost, multipurpose sensor nodes in wireless sensor networks. In sensor networks, the network layer handles routing problems. Since radio transmission requires a significant amount of energy, it is essential to investigate power efficiency and optimization. As a result, the conservation of energy is a critical concern in wireless sensor networks. Recent research is focused on developing routing algorithms that use less amount of energy during communication, thereby prolonging the network’s life. Wireless sensor networks with energy recovery nodes use nodes that can extract energy from their environment. The fuzzy-GWO method and the energy-saving routing algorithm are proposed and analyzed in this research work. For simulation, the MATLAB 2021b working environment is used. The LEACH, HEED, MBC, FRLDG protocols, along with the proposed protocol F-GWO, are compared. From the obtained results, it is found that the network lifetime is increased by 20%, 14.8%, 12.5%, and 3.8%, respectively. In addition, the proposed method has a 37.5%, 33.3%, 16.6%, and 6.25% reduction in average energy consumption when compared with the conventional algorithms. According to the experimental data obtained through simulation, the proposed F-GWO algorithm outperforms the LEACH, HEED, MBC, and FRLDG in network lifetime, packet delivery ratio, throughput, bit error rate (BER), buffer occupancy, time analysis, and end-to-end delay.

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Section: Introductionmentioning

confidence: 99%

Energy-Efficient Clustering and Routing Algorithm Using Hybrid Fuzzy with Grey Wolf Optimization in Wireless Sensor Networks

Singh

Deepika²,

Din

et al. 2022

Security and Communication Networks

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“…Although LEACH has improved the lifetime of the network, random selection can select CH with low energy and lead to significant energy loss and energy hole formation. Hence, variants of LEACH aim to address this limitation by using more efficient parameters to select CHs such as residual energy, density, or distance to BS [10][11][12].…”

Section: Related Workmentioning

confidence: 99%

Untitled

2021

JST: SSAD

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Wireless sensor networks (WSN) play an important role in IoT (Internet of Things) as an interconnecting infrastructure. Working with a limited energy source, the vital challenge for WSN is to prolong the network lifetime as an important performance metric. Furthermore, the limitations of regular transmission technologies create localized network areas of a multi-hop fashion form that adds more constraints to enhance the network performance. Hence, the clustering strategies initially have solved these problems and received the attention of many studies, an approach using unequal clustering strategy has yielded some positive results since consumed energy gaps are avoided in regions near base stations. However, the routing strategy among cluster heads in multi-hop wireless networks is still a big challenge because of its inefficiency in energy consumption aspects. Therefore, in this paper, we propose a novel method that combining an unequal clustering problem and a simple multi-hop routing to prolong network life. The numerical results show that the proposed solution is more effective than other models in recent studies

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“…The energy consumed by node E (t) after period t is given by Equ. (11), 𝑖=1 𝐸(𝑡) = 𝑛(𝑛 𝑡𝑝𝑘𝑡𝑠 * 𝛼) + (𝑛 𝑟𝑝𝑘𝑡𝑠 * 𝛽) (11) where 𝑛𝑡𝑝𝑘𝑡𝑠𝑎𝑛𝑑 𝑛𝑟𝑝𝑘𝑡𝑠is the number of packets transmitted and received.𝛼 𝑎𝑛𝑑 𝛽 are constants in the range of (0, 1).…”

Section: Hybrid Leach With Jellyfishalgorithm For Ch Selectionmentioning

confidence: 99%

“…However, the LEACH protocol, a variation of cluster head-based configuration (CH), has the potential to increase network energy consumption [9,10].The new HEED protocol for nonuniform clusters for the sensor network is expected to improve the network's lifespan. The HEED and the different variants of the existing HEED protocol are performed in energy consumption; the first node dies concerning the cluster radius and the number of live nodes [11]. The selection of optimal cluster head considers four main criteria such distance and residual energy distance between the neighbor node and the central CH.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Clustering in Wireless Sensor Networks using Hybrid Jellyfish Optimization-Leach Protocol

Gurupriya¹,

Sumathi²

2021

DSA

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WSNs are usually equipped with a large number of sensor nodes that are designed and deployed to distribute and distribute the required data. Although sensors are sometimes deployed in remote environments, it is essential to identify a cluster head(CH) with an energy-efficient technique for transferring data in WSN. Cluster head selection algorithm is becoming a significant and challenging problem in WSN. This research presented a hybrid Leach with jellyfish algorithm for cluster head selection and an energy-efficient Heuristic Moth Search Algorithm (HMSA) to find efficient paths for transferring data to base station(BS).This technique avoids congestion with less guaranteed delays and maintain the energy efficiency of WSNs. The cluster head (CH) determines the residual energy on the basis of an optimum fit function assessed on the basis of strategic parameters such as distance between adjacent nodes and the centre. It can significantly reduce the number of dead nodesand reduce energy consumption. The HMSA method has been used to determine the best route for data transfer to the base station once the CH selection is complete. The entire WSN field is divided into several subdivisions, and each section chooses the designated target by measuring the transmission distance. The proposed approach has been assessed analytically, and results are compared with those related to conventional methods, namely HEED, FACER and EACBM, in terms of WSN Quality of service (QoS). The suggested approach demonstrated better performance in the number of live nodes and energy consumption than conventional algorithms.

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A Novel HEED Protocol for Wireless Sensor Networks

Cited by 57 publications

References 12 publications

Energy-Efficient Clustering and Routing Algorithm Using Hybrid Fuzzy with Grey Wolf Optimization in Wireless Sensor Networks

Energy-Efficient Clustering and Routing Algorithm Using Hybrid Fuzzy with Grey Wolf Optimization in Wireless Sensor Networks

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Dynamic Clustering in Wireless Sensor Networks using Hybrid Jellyfish Optimization-Leach Protocol

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