| Autor: |
Hicham Ouchitachen, Abdellatif Hair, Najlae Idrissi |
| Jazyk: |
angličtina |
| Rok vydání: |
2017 |
| Předmět: |
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| Zdroj: |
Egyptian Informatics Journal, Vol 18, Iss 1, Pp 45-54 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
1110-8665 |
| DOI: |
10.1016/j.eij.2016.06.001 |
| Popis: |
In Wireless Sensor Networks (WSNs), the network’s performance is usually influenced by energy constraint. Through a well-designed clustering algorithm, WSN’s energy consumption can be decreased evidently. In this paper, an Improved Multi-Objective Weighted Clustering Algorithm (IMOWCA) is proposed using additional constraints to select cluster heads in WSN. IMOWCA aims at handling a WSN in some critical circumstances where each sensor satisfies its own mission depending on its location. In addition to fulfill its mission, the sensor tries to improve the quality of communication with its neighboring nodes. Our proposed algorithm divides the network into different clusters and selects the best performing sensors based on residual energy to communicate with the Base Station (BS). IMOWCA uses four critical parameters: ECi: Energetic Characteristic of sensor i, DDi: Degree Difference of sensor i, DCi: Sum of distances between sensor i and its neighbors and DMi: Mission distance of sensor i. To balance the consumed energy in different formed clusters, a Base Station Genetic Algorithm (BGA) is developed. Simulation results demonstrate that the proposed algorithms are advantageous in terms of convergence to the appropriate locations and efficients in regard to energy conservation in WSNs. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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