Optimal Coverage of Wireless Sensor Networks Based On Artificial Algae Algorithm (AAA)

Year 2019, Volume: 4 Issue: 2, 117 - 127, 01.12.2019

Ersin Kaya Wakass Saad Jaber

Abstract

In the past few years, the demand for wireless sensor networks has increased significantly due to its small size, low cost and high efficiency. It has been used in many applications and in multiple fields. Owing to the ever-increasing number of applications using the wireless sensor network, it was necessary to find solutions to the problems and challenges faced by the wireless sensor network. One of the important challenges faced by Wireless Network Sensor is coverage. The nodes bear the actual liability to cover the pre-defined region. That's means the sensor nodes is placed in such a way as to achieve the maximal coverage of the area. Artificial alga algorithm (AAA), which is a very effective optimization method, has been used to find the suitable solutions for the coverage problem. The results were compared with the results of three algorithms (Artificial bee colony algorithm (ABC), particle swarm optimization algorithm (PSO) & Differential evolution Algorithm (DE)) to address the coverage problem. AAA proved to be more effective in solving the coverage problem. The simulation of the algorithms is performed by MATLAB and the results are analyzed to show the effectiveness of the proposed algorithm. 

Keywords

Artificial algae algorithm, Coverage Problem, Wireless Sensor network

Optimal Coverage of Wireless Sensor Networks Based On Artificial Algae Algorithm (AAA)

Abstract

In the past
few years, the demand for wireless sensor networks has increased significantly
due to its small size, low cost and high efficiency. It has been used in many
applications and in multiple fields. Owing to the ever-increasing number of
applications using the wireless sensor network, it was necessary to find
solutions to the problems and challenges faced by the wireless sensor network.
One of the important challenges faced by Wireless Network Sensor is coverage.
The nodes bear the actual liability to cover the pre-defined region. That's
means the sensor nodes is placed in such a way as to achieve the maximal
coverage of the area. Artificial alga algorithm (AAA), which is a very
effective optimization method, has been used to find the suitable solutions for
the coverage problem. The results were compared with the results of three
algorithms (Artificial bee colony algorithm (ABC), particle swarm optimization
algorithm (PSO) & Differential evolution Algorithm (DE)) to address the
coverage problem. AAA proved to be more effective in solving the coverage
problem. The simulation of the algorithms is performed by MATLAB and the
results are analyzed to show the effectiveness of the proposed algorithm. 

Keywords

Artificial algae algorithm, Coverage Problem, Wireless Sensor network

References

• P. Rawat, K. D. Singh, H. Chaouchi, and J. M. Bonnin, "Wireless sensor networks: a survey on recent developments and potential synergies," The Journal of supercomputing, vol. 68, no. 1, pp. 1-48, 2014.
• P. Harrop and R. Das, "Wireless sensor networks (wsn) 2012-2022: Forecasts, technologies, players-the new market for ubiquitous sensor networks (usn)," IDTechEx, Tech. Rep., 2012.
• N. Kukunuru, B. R. Thella, and R. L. Davuluri, "Sensor deployment using particle swarm optimization," International Journal of Engineering Science and Technology, vol. 2, no. 10, pp. 5395-5401, 2010.
• R. Mulligan and H. M. Ammari, "Coverage in wireless sensor networks: A survey," Network Protocols and Algorithms, vol. 2, no. 2, pp. 27-53, 2010.
• P. N. Ngatchou, W. L. Fox, and M. A. El-Sharkawi, "Distributed sensor placement with sequential particle swarm optimization," in Swarm Intelligence Symposium, 2005. SIS 2005. Proceedings 2005 IEEE, 2005, pp. 385-388: IEEE.
• N. A. A. Aziz, A. W. Mohemmed, M. Y. Alias, K. A. Aziz, and S. Syahali, "Coverage maximization and energy conservation for mobile wireless sensor networks: A two phase particle swarm optimization algorithm," in Bio-Inspired Computing: Theories and Applications (BIC-TA), 2011 Sixth International Conference on, 2011, pp. 64-69: IEEE.
• S. Mini, S. K. Udgata, and S. L. Sabat, "A Heuristic to Maximize Network Lifetime for Target Coverage Problem in Wireless Sensor Networks," Adhoc & Sensor Wireless Networks, vol. 13, 2011.
• Z. Lu, W. W. Li, and M. Pan, "Maximum lifetime scheduling for target coverage and data collection in wireless sensor networks," IEEE Transactions on vehicular technology, vol. 64, no. 2, pp. 714-727, 2015.
• A. K. Idrees, K. Deschinkel, M. Salomon, and R. Couturier, "Multiround distributed lifetime coverage optimization protocol in wireless sensor networks," The Journal of Supercomputing, vol. 74, no. 5, pp. 1949-1972, 2018.
• F. Carrabs, R. Cerulli, M. Gentili, and A. Raiconi, "Maximizing lifetime in wireless sensor networks with multiple sensor families," Computers & operations research, vol. 60, pp. 121-137, 2015.
• A. Sangwan and R. P. Singh, "Survey on coverage problems in wireless sensor networks," Wireless Personal Communications, vol. 80, no. 4, pp. 1475-1500, 2015.
• K. Deschinkel, "A column generation based heuristic for maximum lifetime coverage in wireless sensor networks," in SENSORCOMM'11, 5-th Int. Conf. on Sensor Technologies and Applications, 2015, pp. 209--214.
• F. Carrabs, R. Cerulli, C. D’Ambrosio, and A. Raiconi, "Extending lifetime through partial coverage and roles allocation in connectivity-constrained sensor networks," IFAC-PapersOnLine, vol. 49, no. 12, pp. 973-978, 2016.
• S. K. Udgata, S. L. Sabat, and S. Mini, "Sensor deployment in irregular terrain using artificial bee colony algorithm," in Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, 2009, pp. 1309-1314: IEEE.
• S. A. Uymaz, G. Tezel, and E. Yel, "Artificial algae algorithm with multi-light source for numerical optimization and applications," Biosystems, vol. 138, pp. 25-38, 2015.