# Optimization of Submodularity and BBO-Based Routing Protocol for Wireless Sensor Deployment
## 5 Conclusions  
In order to reduce costs and save energy, this paper proposes a large-scale sensor deployment method called the IHACA-COpSPIEL algorithm and a routing protocol based on the BBO algorithm. Mutual information is introduced to describe the correlation between observed points and unobserved points, a mathematical model with submodularity is established, and the edges of graph theory are used to represent communication costs. The pSPIEL algorithm with enhanced optimization ability by a chaos operator and the ant colony algorithm with improved heuristic function and pheromone update mechanism are used to find the optimal path. What has been studied can further solve the sensor deployment problem under the constraint of communication cost. Finally, the BBO algorithm-based routing protocol transmits data to the deployed sensors. The computational complexity of the IHACA-COpSPIEL is \(O(kN^{2})\), and the computational complexity of the routing protocol based on the BBO algorithm is \(O(qn^{2})\). The experiments show that the deployment algorithm proposed in this paper has better sensor deployment capabilities. This deployment algorithm reduces the communication cost by 38.42% compared with the greedy algorithm. It also reduces the number of sensors and has a longer life cycle. Compared with the LEACH protocol, the BBO algorithm-based routing protocol has  
Figure 5: Comparison of dead nodes under two protocols.  
Figure 6: Comparison of residual energy under two protocols.  
lower energy consumption and longer network life.  
In the future, we intend to use a discrete event simulator (DES) such as NS-3 to further combine practical application scenarios to improve the effectiveness of the algorithm. Our vision for future work is as follows.  
We will complete the IHACA-COpSPIEL protocol design in the NS-3. We will refer to the RFC document of Multi-Protocol Label Switching protocol, and elaborate on the design and implementation of each basic component of IHACA-COpSPIEL, including the forwarding equivalence class (FEC), next hop label forwarding entry (NHLFE), FEC to NHLFE mapping (FTN), etc. By statically configuring the label forwarding table, the communication between private networks through the backbone network by IHACA-COpSPIEL forwarding will be realized.  
Conceptualization, Y.W., Y.D.; methodology, Y.W., L.W.; software, Y.W., Y.D.; visualization, Y.D., W.D.; investigation, Y.D., W.D.; validation, Y.D., Q.C.; data curation, Q.C., L.W.; original draft preparation, W.D., Q.C.; supervision, Y.W. All authors have read and agreed to the published version of the manuscript.  
This study is funded by Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao (Grant number 61828601), Natural Science Foundation of Shanxi Province(Grant number 201801D121141), and Provincial Program on Key Research Projects of Shanxi (Social Development Area) (Grant number 201903D321003).  
We thank the reviewers for their very helpful comments on improving the paper and pertinent suggestions on our future work.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
BBO Biogeography-Based Optimization IHACA Improved Heuristic Ant Colony Algorithm pSPIEL Darded Sensor Placements at Informative and cost-Effective Locations IHACA-COpSPIEL Improved Heuristic Ant Colony Algorithm-Chaos Optimization of padded Sensor Placements at Informative and cost-Effective Locations SIVs Suitable Index Variables