A Dynamically Reconfigurable Wireless Sensor Network Testbed for Multiple Routing Protocols

Jiang, Wenxian; Gu, Chenzhe; Wu, Jingjing

doi:10.1155/2017/1594270

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…A lot of work has been done through academia and industry personals as we have reviewed from literature in different constraints fields of WSN, 10,11,[17][18][19] but still, we have lots of potential to work in this field due to interdisciplinarity integration of IoT. In this paper, we are motivated by some constraints like node heterogeneity, node energy, energy consumption, and node deployment in the field.…”

Section: Motivationmentioning

confidence: 99%

Energy efficient and effective node deployment for wireless sensor network

Gupta¹,

Kumar²,

Tyagi

2022

Int J Communication

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Summary The development of tiny sensor nodes (SNs) has incarnated numerous applications in the field of wireless sensor networks (WSN). These devices became much popular in multidisciplinary research area such as the internet of things (IoT). However, the use of these devices has been restricted due to some constraints like SN energy, data aggregation, quality of service (QoS), reliability, SN deployment, scalability, energy consumption, and many more. Among all these constraints, we focus on SN energy, SN deployment, and energy consumption of the network. Because if the consumption of SN energy is less, network lifetime automatically increases. So, we propose active–passive node topology on deployed SNs which enhance the network lifetime. With the help of the proposed mechanism, the lifetime and stability have increased by 60% and 3%, respectively, as compared with directed diffusion protocol in Experiment 1. In another experiment, the lifetime has increased by 67%, 64%, and 62% as compared with LEACH, NEAP, and DREEP, respectively, in homogeneous environment. The proposed scheme also performed significant improvement in heterogeneous environment. The simulation performance shows that the proposed protocol increases the network lifetime and stability of the network.

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Section: Motivationmentioning

confidence: 99%

Energy efficient and effective node deployment for wireless sensor network

Gupta¹,

Kumar²,

Tyagi

2022

Int J Communication

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“…en, the task mapping is converted into the optimal solution problem of the task mapping to the node energy consumption under multiple constraints, and the mathematical model is established. From the number of iterations, we use the dynamic weight factor that decreases linearly with the number of iterations to obtain the model node with the least energy consumption, and then, we use the near-node principle to map the resource-heavy tasks required for multiple nodes to work together and finally complete the mapping operating [15].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Resource Allocation and Forecast of Snow Tourism Demand Based on Multiobjective Optimization Algorithm

Feng

Zhang

Dong

2022

Computational Intelligence and Neuroscience

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This paper aims to map the task of reliable transmission of wireless sensor networks. At the same time, this paper transforms the mapping problem of wireless sensor networks into a problem of reducing the energy consumption of mapping under many constraints such as reliability and scheduling length and uses discrete particle swarm optimization algorithm to map. For optimization, the algorithm performs iterative calculations to obtain the best mapping node for each operation so that the inertia coefficient of the existing particle swarm optimization algorithm is improved and linearly minimized with the number of iterations. When resource-demanding tasks need to allocate dynamic resources to multiple nodes to complete collaboratively, adding the mapping principle of the nearest node in the discrete particle swarm optimization mapping reduces the energy consumption of communication between tasks. An in-depth analysis of the influencing factors of the ice and snow tourism market shows that the per capita disposable income of urban residents and the number of urban residents have a significant impact on the ice and snow tourism market demand. In addition, regression analysis and demand-based forecasting are important methods to analyze the scale and development trend of tourism. At the same time, it shows an important position in the purpose of urban tourism and regional market share so as to provide a basis for decision-making in tourism destination marketing. This paper mainly studies and analyzes the wireless sensor network and further introduces it into dynamic resource allocation and ice and snow tourism, which can promote the continuous development of dynamic resource allocation and ice and snow tourism.

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“…WSN has a great application future in the military and civil area. The fundamental problems of sensor networks are deployment and coverage, localization, and networking protocols [1][2][3]. The accuracy of node localization is crucial for many applications of distributed sensor network (DSN) [4][5][6][7].…”

Section: Background and Researchmentioning

confidence: 99%

Wireless Sensor Network Dynamic Mathematics Modeling and Node Localization

Liu

2018

Wireless Communications and Mobile Computing

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With the rapid development of wireless sensor network (WSN) technology and its localization method, localization is one of the basic services for data collection in WSN. The localization accuracy often depends on the accuracy of distance estimation. Because of the constraint in size, power, and cost of sensor nodes, the investigation of efficient location algorithms which satisfy the basic accuracy requirement for WSN meets new challenges. This paper proposes a novel intelligent node localization algorithm in WSN based on beacon nodes to improve the precision in location estimation. Firstly, system model of WSN node localization is constructed according to the WSN environment. Then traditional WSN node localization methods such as DV-HOP, GA, and PSO are studied. Localization algorithm of WSN is proposed by using dynamic mathematics modeling. And the result of simulation, which is compared to the traditional algorithm, indicated that this algorithm is better to improve the accuracy and coverage of WSN. The simulation results show that the performance of the proposed WSN location algorithm is better than the traditional localization algorithms.

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A Dynamically Reconfigurable Wireless Sensor Network Testbed for Multiple Routing Protocols

Cited by 4 publications

References 20 publications

Energy efficient and effective node deployment for wireless sensor network

Energy efficient and effective node deployment for wireless sensor network

Dynamic Resource Allocation and Forecast of Snow Tourism Demand Based on Multiobjective Optimization Algorithm

Wireless Sensor Network Dynamic Mathematics Modeling and Node Localization

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