ABSTRACT
Designing a Wireless Sensor Networks (WSN) mostly was a great challenge. Shown in previous results, some design approaches lead to problems in its implementation. Deterministic methods face the NP-Hard complex problem. On the other side, heuristic methods sometimes produce a flawed result. With those situations, this research concern with exploring the possibility of a multi-objective optimization (MOO) method. As with the MOO method, some conflicted WSN aspects consider simultaneously. Started with the PSO algorithm, this developing method tries to find the best position of the WSN's relays. Closed neighbor sensor nodes are then will be connected. It is combined with the graph to constructs the best communication link. These steps will be done in a certain number of iterations to enhance fault-tolerance ability. This MOO approached method was implemented to different WSN topologies, with several sensors placed in a simulation area. Used as controls are Steiner Point and Triangular Grid algorithms. The most significant finding is this developing method gave some early potential results that could form future solutions in the multi-objective optimization approach for the WSN designing.
- Chaofan Ma, Wei Liang, Meng Zheng, and Hamid Sharif, "A Connectivity-Aware Approximation Algorithm for Relay Node Placement in Wireless Sensor Networks", IEEE Sensors Journal, January 2016.Google Scholar
- Satyajayant Misra, Seung Don Hong, Guoliang Xue, and Jian Tang, "Constrained Relay Node Placement in Wireless Sensor Networks: Formulation and Approximations", IEEE/ACM Transactions on Networking, Volume 18 No.2, 2010. Google ScholarDigital Library
- Dejun Yang, Satyajayant Misra, Xi Fang, Guoliang Xue, and Junshan Zhang, "Two-Tiered Constrained Relay Node Placement in Wireless Sensor Networks: Computational Complexity and Efficient Approximations", IEEE Transactions on Mobile Computing, Volume 11 No. 8, 2012. Google ScholarDigital Library
- Errol L. Lloyd and Guoliang Xue, "Relay Node Placement in Wireless Sensor Networks", IEEE Transaction on Computers, Volume 56 No.1, pp 134--138, 2007. Google ScholarDigital Library
- Miloud Bagaa, Ali Chelli, Djamel Djenouri, Tarik Taleb, Ilangko Balasingham and Kimmo Kansanen, "Optimal Placement of Relay Nodes Over Limited Positions in Wireless Sensor Networks", IEEE Transactions on Wireless Communication, Volume 16 No.4, 2017. Google ScholarDigital Library
- Peng Cheng, Chen-Nee Chuah, Xin Liu, "Energy-aware Node Placement in Wireless Sensor Networks", IEEE Communications Society Globecom, pp 3210--3214, 2004.Google Scholar
- Ali Chelli, Miloud Bagaa, Djamel Djenouri, Ilangko Balasingham, and Tarik Taleb, "One-Step Approach for Two-Tiered Constrained Relay Node Placement in Wireless Sensor Networks", IEEE Wireless Communication Letters, Volume 5 No.4, 2016.Google ScholarCross Ref
- Bo Sheng, Qun Li and Weizhen Mao, "Optimize Storage Placement in Sensor Networks", IEEE Transactions on Mobile Computing, Volume 09, No. 10, October 2010. Google ScholarDigital Library
- Cun Cheng Lin, Lei Shu, and Der Jiunn Deng, "Router Node Placement with Service Priority in Wireless Mesh Networks Using Simulated Annealing with Momentum Terms", IEEE Systems Journal, Volume 10 No. 4, 2016.Google ScholarCross Ref
- Ines Khoufi, Pascale Minet, Anis Laouiti, "Fault-Tolerant and Constrained Relay Node Placement in Wireless Sensor Networks", IEEE 13th International Conference on Mobile Ad Hoc and Sensor Systems, 2016.Google Scholar
- Kai Ding, Homayoun Yousefi'zadeh, "A Systematic Node Placement Strategy for Multi-Tier Heterogeneous Network Graphs", IEEE Wireless Communications and Networking Conference - Track 3 - Mobile and Wireless Networks, 2016.Google Scholar
- Milen Nikolov and Zygmunt J. Haas, "Relay Placement in Wireless Networks: Minimizing Communication Cost", IEEE Transactions on Wireless Communications, Volume 15 No.5, 2016.Google ScholarCross Ref
- Shinji Sakamoto, Tetsuya Oda, Makoto Ikeda, Leonard Barolli, Fatos Xhafa, and Isaac Woungang, "Node Placement in Wireless Mesh Networks: A Comparison Study of WMN-SA and WMN-PSO Simulation Systems", 19th International Conference on Network-Based Information Systems, 2016.Google Scholar
- Changlin Yang, Kwan-Wu Chin, "On Nodes Placement in Energy Harvesting Wireless Sensor Networks for Coverage and Connectivity", IEEE Transactions on Industrial Informatics, pp 1--6, 2016.Google Scholar
- Osama Moh'd Alia and Alaa Al-Ajouri, "Maximizing Wireless Sensor Network Coverage with Minimum Cost Using Harmony Search Algorithm", IEEE Sensors Journal, Volume 17 No. 3, 2017.Google ScholarCross Ref
- Armeline Dembo Mafuta, Tom Walingo, and Telex M. N. Ngatched, "Energy Efficient Coverage Extension Relay Node Placement in LTE-A Networks", IEEE Communication Letters, Volume 21 No. 7, 2017.Google ScholarCross Ref
- Djamel Djenouri and Miloud Bagaa, "Energy-Aware Constrained Relay Node Deployment for Sustainable Wireless Sensor Networks", IEEE Transactions on Sustainable Computing, Volume 12 No. 1, 2017.Google ScholarCross Ref
- Satyajayant Misra, Nahid Ebrahimi Majd, and Hong Huang, "Approximation Algorithms for Constrained Relay Node Placement in Energy Harvesting Wireless Sensor Networks", IEEE Transactions on Computers, Volume 63 No. 12, 2014. Google ScholarDigital Library
- Tengjiao He, Kwan Wu Chin, and Sieteng Soh, "On Wireless Power Transfer and Max Flow in Rechargeable Wireless Sensor Networks", IEEE Access, Volume 4, 2016.Google Scholar
- Arouna Ndam Njoya, Christopher Thron, Jordan Barry, Wahabou Abdou, Emmanuel Tonye, Nukenine Siri Lawrencia Konje, and Albert Dipanda, "Efficient Scalable Sensor Node Placement Algorithm for Fixed Target Coverage Applications of Wireless Sensor Networks", IET Wireless Sensors Systems, Volume 7 No.2, 2017.Google Scholar
- Subir Halder and Amrita Ghosal, "A Location-Wise Predetermined Deployment for Optimizing Lifetime in Visual Sensor Networks", IEEE Transaction on Circuits and Systems for Video Technology, Volume 26, No. 6, June 2016.Google ScholarCross Ref
- Jones, D. F., Mirrazavi, S. K., & Tamiz, M. Multiobjective meta-heuristics: An overview of the current state-of-the-art. European Journal of Operational Research, 137, 1--9. (2002).Google ScholarCross Ref
- Bin Cao, Jianwei Zhao, Zhihan LV, Xin Liu, Shan Yang, Xinyuan Kang, and Kai Kang, "Distributed Parallel Particle Swarm Optimization for Multi-Objective and Many-Objective Large-Scale Optimization", IEEE Access, Volume 5, Mei 2017.Google Scholar
- Nor Azlina Abdul Aziz, Kamarulzaman Abdul Aziz, and Wan Zakiyah Wan Ismail, "Coverage Strategies for Wireless Sensor Networks", World Academy of Science Engineering and Technology, Volume 50, 2009.Google Scholar
- Zhen Hu, Dexuan Zou, Zhi Kong, and Xin Shen, "A Particle Swarm Optimization Algorithm with Time Varying Parameters", Proceedings of the 30th Chinese Control and Decision Conference CCDC, 2018.Google Scholar
Index Terms
- Relay nodes placement for optimal coverage, connectivity, and communication of wireless sensor networks: a PSO-based multi-objective optimization research idea
Recommendations
Multi-Tier Topology Design of Wireless Sensor Networks using Multi-Objective Particle Swarm Optimization
SIET '22: Proceedings of the 7th International Conference on Sustainable Information Engineering and TechnologyIn WSN, node placement is the most fundamental and growing topic since the location and function of the nodes define network performance. Recently, the placement methods are formulated as an optimization problem and solved by multi-objective ...
Relay Node Placement in Wireless Sensor Networks
A wireless sensor network consists of many low-cost, low-power sensor nodes, which can perform sensing, simple computation, and transmission of sensed information. Long distance transmission by sensor nodes is not energy efficient since energy ...
Integrated Connectivity and Coverage Techniques for Wireless Sensor Networks
MobiWac '16: Proceedings of the 14th ACM International Symposium on Mobility Management and Wireless AccessA wireless sensor network (WSN) consists of a group of energy-constrained sensor nodes with the ability of both sensing and communication, which can be deployed in a field of interesting (FoI) for detecting or monitoring some special events and then ...
Comments