A Tabu Search Algorithm for Cluster Building in Wireless Sensor Networks

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.

Existing System:

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.

Proposed System:

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.

Modules:

  • Networking Module

  • Data collection module

  • Tabu search adaptation

  • Diversification and Intensification module

Tools Used:

Front End : Visual Studio Dot Net 2005
Coding Language : C#.NET