Optimal topologies for wireless sensor networks

Tillett, Jason C.; Yang, Shanchieh Jay; Rao, Raghuveer M.; Sahin, Ferat

doi:10.1117/12.578518

Cited by 7 publications

(2 citation statements)

References 13 publications

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“…The sum of cognitive and personal components is generally set to four as recommended in [33]. In [34], they are set to 2.8 and 1.3, respectively. Although, based on our experiments, we adopt the values of 1.75 and 1.35, respectively.…”

Section: Pso and Nsga-iii Parametersmentioning

confidence: 99%

A new multi-agent particle swarm algorithm based on birds accents for the 3D indoor deployment problem

et al. 2019

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h i g h l i g h t s• Proving the efficiency of optimization algorithms in solving real-world problems.• A new concept of accent birds introduced to the particle swarm optimization. • A new hybrid scheme that integrates PSO and MAS.• The hybridization improves the performance of the original tested algorithms. • A comparison between simulation and experimental validation is given. a r t i c l e i n f o Keywords: Accent based PSO Multi-agent Many-objective optimization Experimental validation 3D indoor deployment DL-IoT collection networks a b s t r a c tThe 3D indoor deployment of sensor nodes is a complex real world problem, proven to be NP-hard and difficult to resolve using classical methods. In this context, we propose a hybrid approach relying on a novel bird's accent-based many objective particle swarm optimization algorithm (named acMaPSO) to resolve the problem of 3D indoor deployment on the Internet of Things collection networks. The new concept of bird's accent is presented to assess the search ability of particles in their local areas. To conserve the diversity of the population during searching, particles are separated into different accent groups by their regional habitation and are classified into different categories of birds/particles in each cluster according to their common manner of singing. A particle in an accent-group can select other particles as its neighbors from its group or from other groups (which sing differently) if the selected particles have the same expertise in singing or are less experienced compared to this particle. To allow the search escaping from local optima, the most expert particles (parents) ''die'' and are regularly replaced by a novice (newborn) randomly generated ones. Moreover, the hybridization of the proposed acMaPSO algorithm with multi-agent systems is suggested. The new variant (named acMaMaPSO) takes advantage of the distribution and interactivity of particle agents. Experimental, numerical and statistical found results show the effectiveness of the two proposed variants compared to different other recent state-of-the-art of many-objective evolutionary algorithms.✩ This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. * Correspondence to: bureau C107, Batiment C, 1 Place Georges positions and the topology of the network. In this study, we are interested in the deployment of nodes in a three-dimensional space that reflects the real topology of the RoI (region of interest) better than the two-dimensional case. We are particularly interested in improving the initial 3D indoor deployment by adding new nodes while optimizing a set of objectives such as coverage, connectivity, localization, quality of links and network utilization. These objectives will be detailed in the modeling section. To resolve the deployment problem in WSN, the topology of the network can be modeled as an identification problem in a graph as addressed in [1] and [2]. In this static case, the deployment algorithm is run off-...

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Section: Pso and Nsga-iii Parametersmentioning

confidence: 99%

A new multi-agent particle swarm algorithm based on birds accents for the 3D indoor deployment problem

et al. 2019

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“…To decrease the loss of energy and data packets, a clustertree network topology structure (Tillett et al, 2004) (shown as Fig. 1) is applied in this design.…”

Section: Main Parameters Of Forest Fire Monitormentioning

confidence: 99%

Forest fire detection system based on a ZigBee wireless sensor network

et al. 2008

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Compared with the traditional techniques of forest fire detection, a wireless sensor network paradigm based on a ZigBee technique was proposed. The proposed technique is in real time, given the exigencies of forest fires. The architecture of a wireless sensor network for forest fire detection is described. The hardware circuitry of the network node is designed based on a CC2430 chip. The process of data transmission is discussed in detail. Environmental parameters such as temperature and humidity in the forest region can be monitored in real time. From the information collected by the system, decisions for fire fighting or fire prevention can be made more quickly by the relevant government departments.

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Data Aggregation in Wireless Sensor Network Using Shuffled Frog Algorithm

Abirami¹,

Anandamurugan²

2015

Wireless Pers Commun

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Optimal topologies for wireless sensor networks

Cited by 7 publications

References 13 publications

A new multi-agent particle swarm algorithm based on birds accents for the 3D indoor deployment problem

A new multi-agent particle swarm algorithm based on birds accents for the 3D indoor deployment problem

Forest fire detection system based on a ZigBee wireless sensor network

Data Aggregation in Wireless Sensor Network Using Shuffled Frog Algorithm

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