The impact of error control schemes on lifetime of energy harvesting wireless sensor networks in industrial environments

Tekin, Nazli; Güngör, Vehbi Çağrı

doi:10.1016/j.csi.2020.103417

Cited by 19 publications

(4 citation statements)

References 15 publications

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“…In the study (32,33) the author has showed that the DE is best suited for all the newly emerging problems that are related to optimization. In the study (34,35) it was highlighted that the HAS and MHSA suffers from problem of fixed pitch adjustment rate that causes uncertainty resulting in local optimum value and random search directions slows down the convergence towards https://www.indjst.org/ optimum value. The limitations of HAS and MHAS can be overcome using DE by increasing the local search capacity using population multiplicity (36,37) .…”

Section: Related Workmentioning

confidence: 99%

An efficient hybrid model for cluster head selection to optimize wireless sensor network using simulated annealing algorithm

Umashankar¹,

Anitha²,

Mallikarjunaswamy³

2021

IJST

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Objective: Energy efficiency aspect in wireless sensor networks (WSN) can be achieved by small sized rechargeable and easily replaceable batteries. The lifetime of wireless sensor network can be improved by identifying the efficient and reliable nodes as a cluster heads using Hybrid Simulated Annealing algorithm. The proposed algorithm identifies cluster head to reduce overhead and is capable of handling high volume of nodes with minimum node death rate. Methods: This study proposed initialization of population vectors using the opposite point procedure, self-adaptive control approach by node mutation rate, crossover rate, node capacity and cluster head allocation Methods. Findings: A case study in the proposed work is found to be better in throughput, accuracy, efficiency, energy utilization, batteries recharge ability and replacement procedures compared to the conventional methods. By the analysis and comparison of the proposed method with existing methods, it is identified that the reduction of the number of dead nodes gradually increases the throughput and lifetime of the nodes with respect to the number of iterations. Novelty: To overcome the limitations of conventional Low Energy Adaptive Clustering Hierarchy (LEACH), harmony search algorithm (HSA), modified HSA and differential evolution, we propose a hybrid optimal model using simulated annealing algorithm which includes a node capability function. It is used to improve the network lifetime of the cluster heads and sensor nodes. The proposed method have capability of batteries recharge ability and replacement option to improve network throughput and reliability of network.

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Section: Related Workmentioning

confidence: 99%

An efficient hybrid model for cluster head selection to optimize wireless sensor network using simulated annealing algorithm

Umashankar¹,

Anitha²,

Mallikarjunaswamy³

2021

IJST

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“…Another category of techniques explores the impact of implementing data processing algorithms on the EHS nodes' lifetimes. Data compression 16 and error correction code 17 have been investigated. The study shows that reducing the data packet size before transmission improves the nodes' lifetimes as the energy consumed while processing data is significantly less than the energy required while transmission.…”

Section: Related Workmentioning

confidence: 99%

Judicious data management for sustaining an energy harvesting sensor node

Singh

Shukla

Sachin

et al. 2020

Concurrency and Computation

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Summary Perpetual lifetimes and low maintenance are few of the attractive aspects of sensor nodes that harvest ambient energy. However, their operation depends heavily on the energy profiles of their harvesting source(s). In this work, we study the suitability of energy harvesting sensor (EHS) Nodes, powered using indoor lighting and vibrations, for a simple temperature monitoring application. To help these nodes sustain, we have proposed schemes that allow the nodes to sample and transmit data judiciously. Along with an adaptive sampling based on autoregressive (AR) model, we have proposed a regulating function based transmission scheme that regulates the amount of transmitted data based on the energy available at the node and the characteristics of the data so that even with limited transmissions the fidelity of the data is not lost. With the help of thorough evaluations, we can conclude that an EHS node fares quite well. Results show that adaptive sampling and transmissions based on regulating function not only save energy at the sensor nodes, but they also reduce the amount of data generated and accumulated in a network.

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“…A novel On-demand, an OPTIC algorithm for WSNs was proposed. In 2020, Nazli Tekin and Vehbi Cagri Gungor [3], presented lifetime analysis for error control techniques that were FEC, ARQ, and HARQ in diverse industrial environment channel circumstances. Moreover, the effect of energy yielded techniques on the lifetime of the network was examined.…”

Section: Literature Reviewmentioning

confidence: 99%

Sensor Activation in WSN using Improved Cuckoo Search and Squirrel Search Algorithm

Maqbali¹

2020

JNACS

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In Wireless Sensor Network (WSN), the development is augmented and an increased enormous concentration in computer vision. A huge amount of sensors are used to carry out dispersed sensing of the target field in WSN. The existing techniques exploited wireless chargers to provide energy to Sensor Networks (SNs), other than supplied energy is not adequate to control the sensor nodes. Hence, this work presents a method to reduce the energy utilization per node adopting effectual scheduling of sleep/awake of nodes. The technique experiences two stages for the sensor activation such as the initialization stage, and the activation stage. The initialization stage is proposed by a network beginning that is performed to express the network parameters to nodes or sensors. Subsequently, in every slot proposed optimization method is used to activate sensors in the activation stage. The proposed improved cuckoo search and squirrel search optimization approach named (Improved CS-SSA). Hence, the proposed technique produces control in terms of the turn-ON or OFF of sensors that represent active sensors and employ itself in sensing and monitoring distributed environment. The proposed technique performance is superior to other existing techniques through throughput, maximum energy, and alive nodes, correspondingly.

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The impact of error control schemes on lifetime of energy harvesting wireless sensor networks in industrial environments

Cited by 19 publications

References 15 publications

An efficient hybrid model for cluster head selection to optimize wireless sensor network using simulated annealing algorithm

An efficient hybrid model for cluster head selection to optimize wireless sensor network using simulated annealing algorithm

Judicious data management for sustaining an energy harvesting sensor node

Sensor Activation in WSN using Improved Cuckoo Search and Squirrel Search Algorithm

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