Improvement of lifetime duty cycle using genetic algorithm and network coding in wireless sensor networks

Bhulania, Paurush; Gaur, Nikhil; Federick, Keithellakpam Poirei

doi:10.1109/confluence.2016.7508192

Cited by 7 publications

(2 citation statements)

References 7 publications

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“…In the following sections general terms of GA with their meaning are briefly discussed: has been addressed in [17]. The lifespan enhancement of WSNs using GA is proposed by [18][19].…”

Section: Optimization By Genetic Algorithm In Wireless Sensor Networkmentioning

confidence: 99%

Optimization by Genetic Algorithm in Wireless Sensor Networks Utilizing Multiple Sinks

Solangi

Hakro

Memon

et al. 2019

Mehran Univ. res. j. eng. technol.

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WSN (Wireless Sensor Network) comprises of small-sized and constraint-capability SN (Sensor Nodes) which record, send and receive data, sensed to a sink. The network lifetime and energy usability are important challenges to be dealt with. During the working of the SN, the maximum amount of energy is consumed than sensing and processing of data. Therefore, an efficient transmission of the data is required so that the energy can be saved. In this paper, a novel routing and scheduling method for WSNs using GA (Genetic Algorithm) is presented, where the sinks employed on four sides of the sensor field. These sinks collect the data from the SNs having the optimal distance towards the respective sink. The proposed scheme finds the optimized path using GA, during transmission of data from SN to the nearest sink. First, we run the GA for determination of routing paths, where a source SN finds the possible number of optimal hops. Second, the hops or intermediate relay SNs are assumed to relay the data towards the sink, efficiently. The performance is experimented and evaluated using MATLAB R2016b. The simulations have carried out through comparing the proposed scheme with TEEN (Threshold Sensitive Energy Efficient Sensor Network Protocol). The results of simulation comprise of 10 and 20 number of SNs, discretely. Additionally, the direct distance of each node is calculated and the distance through multiple hops from/to the nearest sink is also evaluated. The achievements of the proposed technique are to save both energy and distance for the sake of network longevity and optimal and precise data delivery by multiple hops.

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“…In the following sections general terms of GA with their meaning are briefly discussed: has been addressed in [17]. The lifespan enhancement of WSNs using GA is proposed by [18][19].…”

Section: Optimization By Genetic Algorithm In Wireless Sensor Networkmentioning

confidence: 99%

Optimization by Genetic Algorithm in Wireless Sensor Networks Utilizing Multiple Sinks

Solangi

Hakro

Memon

et al. 2019

Mehran Univ. res. j. eng. technol.

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“…reduced-complexity Genetic Algorithm (GA) [52] can be used in Multi-hop networks with two kinds of scheduling algorithms which can be either random or it can be circular. The goal of the scheduler is to group a set of nodes into a cluster and select better clusters heads in an adaptive fashion with the help of genetic.…”

Section: F Transmission and Time Schedulingmentioning

confidence: 99%

Reckoning Network Lifetime Ratio for Wireless Sensor Network

Saqhib¹,

S²

2019

IJITEE

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Advanced Technologies such as Internet of Things, Machine Networking give rise to the deployment of autonomous Wireless Sensor Nodes. They are used for various domains namely battlefield monitoring, enemy detection and monitoring the environment change. These Wireless Sensor Nodes have the properties of low cost and high battery life. NL (Network Lifetime) is an important phase of Wireless Sensor Network (WSNs), in which the nodes can maintain sensing for a more amount of time. NL can be improved by use of multiple techniques namely Opportunistic Transmission, Scheduling of Timed Data Packets, Clustering of Nodes, Energy Harvesting and Connectivity. This paper provides the energy consumption computation, life time ratio definition and the overview of NL improvement techniques. The paper also presents brief review of the Destination based and Source based routing algorithm

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Modeling Pairwise XOR Network Coding In Duty-Cycled Wireless Sensor Networks

Nikolaidis

2017

2017 International Conference on Advanced Computing and Applications (ACOMP)

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Improvement of lifetime duty cycle using genetic algorithm and network coding in wireless sensor networks

Cited by 7 publications

References 7 publications

Optimization by Genetic Algorithm in Wireless Sensor Networks Utilizing Multiple Sinks

Optimization by Genetic Algorithm in Wireless Sensor Networks Utilizing Multiple Sinks

Reckoning Network Lifetime Ratio for Wireless Sensor Network

Modeling Pairwise XOR Network Coding In Duty-Cycled Wireless Sensor Networks

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