Table 3.
Mobile Deployment Algorithm in UWSNs.
| Author | Algorithm | Objective | Deployment Criteria | ||
|---|---|---|---|---|---|
| Energy Consumption |
Coverage | Connectivity | |||
| [35] | Self-deployment Particle swarm | Optimize events coverage | Yes | Yes | Yes |
| [36] | Construction of initial infrastructure | Node placement strategy to minimize transmission cost | No | Yes | Yes |
| [37] | Uneven cluster deployment | Improves network reliability and prolongs network lifetime | Yes | Yes | Yes |
| [38] | Fisher information matrix (FIM) | Target positioning precision | Yes | No | No |
| [39] | A three-dimensional coverage pattern and deployment scheme | Preserve network coverage | Yes | Yes | Yes |
| [32] | Game theory | Optimize mobility of nodes and targets | No | Yes | Yes |
| [40] | Integration of a realistic model and gradient descent method | Improve sensor node placement | Yes | Yes | No |
| [41] | Multiobjective optimization framework | optimal deployment of a sparse network of sensors against moving targets | No | Yes | Yes |
| [42] | Autonomous deployment algorithm for k-barrier coverage | Utilize self-deployment method to improve coverage | Yes | Yes | Yes |
| [43] | Greedy Iterative Approach (GFCND) | Improve network connectivity and coverage | Yes | Yes | Yes |
| [44] | Stratified Connected Tree | Optimize leaf nodes position to improve coverage and connectivity | Yes | Yes | Yes |