The main challenge in wireless sensor network deployment pertains to optimizing energy consumption when collecting data from sensor nodes. Compared to other methods (CPLEX-based method, distributed method, simulated annealing-based method), the results show that our tabu search-based approach returns high-quality solutions in terms of cluster cost and execution time. As a result, this approach is suitable for handling network extensibility in a satisfactory manner.
The main challenge when deploying sensor networks pertains to optimizing the energy consumption for data collection from sensor nodes. A new data collection mechanism based on a centralized clustering method distributed clustering method. It uses sensor network energy maps and applies QoS requirements in order to reduce energy consumption.
This paper proposes a new centralized clustering method for a data collection mechanism in wireless sensor networks, which is based on network energy maps and Quality-of-Service (QoS) requirements. The clustering problem is modeled as a hyper graph partitioning and its resolution is based on a tabu search heuristic. Our approach defines moves using largest size cliques in a feasibility cluster graph.
- Networking module
- Data collection module
- Tabu search adaptation
- Diversification and Intensification module