Characterization of wireless mesh network performance in agricultural environments

Abouzar, Pooyan; Michelson, David G.

doi:10.1109/usnc-ursi.2014.6955507

Cited by 1 publication

(1 citation statement)

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“…Conversely, from experimental and analytical design, this proposed study discovers that node height and transmission power affect signal propagation significantly. Also, [18,19] consider just two factors which are antenna height and distance in their experiments. They do not consider the interaction effect of the factors to know which one has a significant contribution before applying it in their experiments.…”

Section: Figure1 Model Of the Process Or Experimentsmentioning

confidence: 99%

Investigation of Factors that Determine the Performance of Wireless Sensor Systems for Large-scale on Demand Deployment

Olasupo¹,

Olasupo²

2017

ujcn

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Most of the studies done so far consider just one or two factors that determine network behavior during experiment or analysis and reach a conclusion with that. Thereby making wireless sensor system deployment design to incur variability and non-conformance to target requirements, and increase in development time and cost. This study proposes an approach to improve deployment plan for wireless sensor network by considering the most appropriate factors that could contribute significantly to deployment performance. The study specifies some factors and demonstrates how they influence network performance using factorial coding. It also provides demonstration of an optimization approach of implementing the factors-"EASY algorithm-Eliminate, Adjust, Simulate and Yield result" on experimental measurements. This research uses factorial design, polynomial analysis, and hypothesis testing for an experiment to investigate the factors that could determine the performance of the system. Result shows that inclusion of more significant factors in a design model will enhance the model by 26%. Using this approach during pre-deployment design and pre-knowledge of performance factor will help in improving the quality of service and achieve desired aim of system. It will ensure that reliable accurate models are being used in network design, planning, and implementations for improved performance.

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Section: Figure1 Model Of the Process Or Experimentsmentioning

confidence: 99%