An Evolutionary Dynamic Approach for Designing Wireless Sensor Networks for Real Time Monitoring

The evolution in the microelectronics and embedded systems has expanded the employment of Wireless Sensor Networks (WSNs). The energy limitation of the nodes is a very important restriction of those structures and should be always considered during the network design. The search for energy-efficient...

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Bibliographic Details
Main Authors: Martins, Flavio V. C., Carrano, Eduardo G., Wanner, Elizabeth F., Takahashi, Ricardo H. C., Mateus, Geraldo R.
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Batteries
Computer systems organization
Computer systems organization > Dependable and fault-tolerant systems and networks
Electronic mail
evolutionary algorithms
Gallium
General and reference
General and reference > Cross-computing tools and techniques
General and reference > Cross-computing tools and techniques > Performance
Hardware
Hardware > Communication hardware, interfaces and storage
Hardware > Communication hardware, interfaces and storage > Signal processing systems
Heuristic algorithms
Monitoring
Networks
Networks > Network performance evaluation
Networks > Network types
Networks > Network types > Mobile networks
performance evaluation
Wireless sensor networks
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Description
Summary:The evolution in the microelectronics and embedded systems has expanded the employment of Wireless Sensor Networks (WSNs). The energy limitation of the nodes is a very important restriction of those structures and should be always considered during the network design. The search for energy-efficient WSNs must take into account aspects which are essential for the proper operation of the network, such as area coverage and network connectivity. This paper proposes an evolutionary approach for performing the design of WSNs, considering the dynamic nature of the problem. A genetic algorithm, which aims to maximize the lifetime of the network, is employed for establishing the sequence in which the sensor nodes are activated, ensuring that the minimum coverage (established a priori) and the connectivity constraints are met. Results achieved by the proposed algorithm in a 81-sensor node instance are compared with a former work, in order to validate the approach which is presented here.
ISSN:1550-6525
DOI:10.1109/DS-RT.2010.25