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- Title
MBASE: Meta-heuristic Based optimized location allocation algorithm for baSE station in IoT assist wireless sensor networks.
- Authors
Chaurasia, Soni; Kumar, Kamal
- Abstract
In an Internet of Things (IoT) assisted Wireless Sensor Network (WSN), the location of the Base Station (BS) remains important. BS serves as the central hub for data collection, aggregation and communication within the network. Its location significantly impacts the overall network performance and energy efficiency. However, the role and requirements of the BS may vary depending on the specific implementation and integration of IoT assist opportunistic routing protocol. Therefore, this work propose a Meta-heuristic Based optimized location Allocation algorithm for baSE station in IoT assist WSNs (MBASE). The MBASE algorithm is based on Forwarder Node (FN) selection and using meta-heuristic based opportunistic routing. The FN is selected by a decision-making approach based on meta-heuristic search strategies which offers viable options for local and global optimization problems. This work aims to find a way to achieve a trade-off in this algorithm for efficient and appropriate placement of BS either at the centre or outside of the network deployment zone. Both positions of BS are optimization problems in the design of WSNs/IoTs. MBASE algorithm is proposed for identifying the optimized location allocation for BS and is based on metaheuristic. Simulation based analysis of essential operational and functional parameters such as Message Success Rate (MSR), Packet Delivery Ratio (PDR), Throughput, and Average energy consumption (AEC) is reported in the paper. Additionally, work compares BS locations using a common neighbourhood concept to assure fairness. The evaluation shows a significant improvements in the PDR, MSR, Throughput and AEC for two different BS locations.
- Subjects
WIRELESS sensor networks; INTERNET of things; ALGORITHMS; NETWORK performance; TELECOMMUNICATION systems; NETWORK hubs; GLOBAL optimization; TABU search algorithm
- Publication
Multimedia Tools & Applications, 2024, Vol 83, Issue 18, p53383
- ISSN
1380-7501
- Publication type
Article
- DOI
10.1007/s11042-023-17541-w