EE-LEACH: Energy Enhancement in LEACH using Fuzzy Logic for Homogeneous WSN

Dwivedi, Anshu Kumar; Sharma, Awadhesh Kumar

doi:10.1007/s11277-021-08598-7

Cited by 32 publications

(35 citation statements)

References 22 publications

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“…If any SN does not get this message, it automatically elects itself as a CH after each round in which it participates. The paper discusses an energy enhancement in LEACH using fuzzy logic called EE-LEACH [ 33 – 35 ]. This method prolongs the lifespan of WSNs and also performs load balancing using equal energy dissipation.…”

Section: Literature Reviewmentioning

confidence: 99%

An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems

Khan¹,

Singh

Singh³

et al. 2022

Computational Intelligence and Neuroscience

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In today’s environment, electronics technology is growing rapidly because of the availability of the numerous and latest devices which can be deployed for monitoring and controlling the various healthcare systems. Due to the limitations of such devices, there is a dire need to optimize the utilization of the devices. In healthcare systems, Internet of things (IoT) based biosensors networking has minimal energy during transmission and collecting data. This paper proposes an optimized artificial intelligence system using IoT biosensors networking for healthcare problems for efficient data collection from the deployed sensor nodes. Here, an optimized tunicate swarm algorithm is used for optimizing the route for data collection and transmission among the patient and doctor. The fitness function of the optimized tunicate swarm algorithm used the distance, proximity, residual, and average energy of nodes parameters. The proposed method is attributed to the optimal CH chosen under TSA operation having a lower energy consumption. The performance of the proposed method is compared to the existing methods in terms of various metrics like stability period, lifetime, throughput, and clusters per round.

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Section: Literature Reviewmentioning

confidence: 99%

An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems

Khan¹,

Singh

Singh³

et al. 2022

Computational Intelligence and Neuroscience

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“…The proposed protocol provides quite improved performance in terms of energy consumption, network lifetime, and reliability. Anshu Kumar Dwivedi et al, [23] have demonstrated the balanced energy dissipation to overcome the hotspots in WSNs. The authors have been discussed the cluster formation and CH selection based on fuzzy inference systems.…”

Section: Literature Surveymentioning

confidence: 99%

“…The proposed SS-LEACH is simulated, and performance is evaluated using NS2 and compare with SRN-LEACH [24], DEE approach [22], and EE-LEACH [23] mechanism. The random deployment of sensor nodes is included in the network field of 1000𝑚 × 1000𝑚.…”

Section: Simulation Setupmentioning

confidence: 99%

A Secure LEACH Protocol for Efficient CH Selection and Secure Data Communication in WSNs

Sanapala¹,

Duggirala²

2022

IJCNIS

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Due to the applications of wireless sensor networks (WSNs) in distinct fields, like civilian and military, environmental monitoring, and target tracking, etc., it became the important research area for researchers. Therefore, an efficient organization of network topology is needed for multi-hop data aggregation based on the energy constrained WSNs with large scale deployment for making the routing task simpler, balancing the load efficiently, and enhancing the network lifetime. The low-energy adaptive clustering hierarchy (LEACH) is an architecture of application-specific protocol, which is used for WSNs. However, this LEACH protocol suffered from more energy consumption in network without considering the cluster heads (CHs) distribution on a rotation basis. In addition, the complex security mechanisms are not sufficient due to limited bandwidth and other restrictions that the sensor nodes have. Thus, it is essential to improve the energy efficiency, CH stability and secure data transmission in WSN’s, which is the main objective of this work. Motivated from these three challenges, this article proposes a stable and secure LEACH (SS-LEACH), in which a new and improved protocol of LEACH is proposed for enhancing the stability of CH and energy efficiency as it considers the nodes’ consumed energy ratio (CER) for CH selection and random number generation, here after the proposed LEACH is named as CER-LEACH. In addition, it aims to prevent the previously elected CH node and it will get another chance in the current round. This method correlates the threshold used in traditional LEACH with the energy consumption ratio of each node. Further, it also introduces a hybrid reputation-based data transmission (HRDT) scheme for secure data transmission. With the proposed CER-LEACH protocol, WSNs achieves better performance in terms of secured communication, network lifetime, and energy consumption based on the analysis of simulation results as compared to state-of-art approaches.

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“…Many fields are functioning with sensors supports, such as surveillance, home security, hospitals, industrial monitoring, military operations, environmental monitoring, and diminishes human effort 4 . Sensor nodes are expected to last until their energy drains and they are automatically disposable 5 . Consequently, it is vigorous for managing the energy incisively to spread the existence of the sensors for the extent of particular mission 6 .…”

Section: Introductionmentioning

confidence: 99%

“…4 Sensor nodes are expected to last until their energy drains and they are automatically disposable. 5 Consequently, it is vigorous for managing the energy incisively to spread the existence of the sensors for the extent of particular mission. 6 Failures in sensor networks continue to increase due to energy depletion.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Elman spike neural network for cluster head based energy aware routing in WSN

Meenakshi¹,

Karunkuzhali²

2022

Trans Emerging Tel Tech

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An enhanced Elman spike neural network (EESNN) optimized with hybrid wild horse optimization and chameleon swarm algorithm is proposed in this manuscript for multi‐objective cluster head selection and energy aware routing in wireless sensor network (CH‐EESNN‐Hyb‐WH‐CSOA‐WSN). Initially, EESNN is used to intelligent selection of cluster head. Then, the optimal cluster head utilized the selected data transferring process with the consideration of multi‐objective fitness function based EESNN. Here, some of the multi‐objective fitness function factors are considered, like energy, delay, throughput, distance between the nodes, traffic rate and cluster density. The hybrid wild horse optimization and chameleon swarm algorithm (Hyb‐WH‐CSOA) is taken into account for the optimal route path selection with minimal delay. The proposed CH‐EESNN‐Hyb‐WH‐CSOA‐WSN method is activated in network simulator 3 (NS‐3) tool. The performance of the proposed method is examined under certain performance metrics, like count of alive nodes, drop, network lifetime, delay, throughput, energy consumption, and packet delivery ratio. Finally, the proposed method attains 98.78%, 97.21%, 99.61% lower delay, 98.78%, 99.21%, 96.78% higher delivery ratio, and 99.57%, 98.67%, 98.88% lower packet drop compared with the existing methods, like optimal secure cluster head placement through source coding techniques in wireless sensor networks (CHP‐HMC‐WSN), optimal placement of single cluster head in wireless sensor networks via clustering (CHP‐K‐Means C‐PSO‐WSN) and hybrid firefly approach along particle swarm optimization for energy efficient optimum cluster head selection in wireless sensor networks (CHP‐HFAPSO‐WSN) respectively.

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EE-LEACH: Energy Enhancement in LEACH using Fuzzy Logic for Homogeneous WSN

Cited by 32 publications

References 22 publications

An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems

An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems

A Secure LEACH Protocol for Efficient CH Selection and Secure Data Communication in WSNs

Enhanced Elman spike neural network for cluster head based energy aware routing in WSN

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