Energy and Lifetime-based Management of Directional Sensor Network Using Combined Meta-heuristic Optimization of Gray-Wolf and Tabu Search Approaches
محورهای موضوعی : Computer EngineeringPeyman Mokaripoor 1 , Mirsaeid Hosseini Shirvani 2 , hamid reza ghaffary 3 , reza noorian 4
1 - Department of Computer Engineering, Ferdows Branch, Islamic Azad University, Ferdows, Iran
2 - Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran
3 - Department of Computer Engineering, Ferdows Branch, Islamic Azad University, Ferdows, Iran
4 - Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran
کلید واژه: Directional Sensor Network (DSN), Gray-Wolf-Algorithm, Tabu Search,
چکیده مقاله :
Coverage and network lifetime are two important metrics within the directional sensor networks (DSN). One of the well-known methods to increase the network lifetime is to create a set of so-called cover-set (CS) sensors, one of which at any given time interval is responsible for covering all the defined objectives within the network. How to construct these CSs has been the problem investigated in many researches, in all of which, the main goal has been to create more CSs that are best in enhancement of network’s lifespan. In this study, a combination of Gray-Wolf Algorithm (GWO) and Tabu Search (TS) has been used for creation and selection process of CS sensors. In order for performance validation of the proposed hybrid algorithm (HA) against other approaches, computer simulations were implemented. The simulation results illustrated that the proposed HA approach can provide the network with longer lifespan.
Coverage and network lifetime are two important metrics within the directional sensor networks (DSN). One of the well-known methods to increase the network lifetime is to create a set of so-called cover-set (CS) sensors, one of which at any given time interval is responsible for covering all the defined objectives within the network. How to construct these CSs has been the problem investigated in many researches, in all of which, the main goal has been to create more CSs that are best in enhancement of network’s lifespan. In this study, a combination of Gray-Wolf Algorithm (GWO) and Tabu Search (TS) has been used for creation and selection process of CS sensors. In order for performance validation of the proposed hybrid algorithm (HA) against other approaches, computer simulations were implemented. The simulation results illustrated that the proposed HA approach can provide the network with longer lifespan.
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