WSNs, consisting of autonomous, small sensors with limited battery power, can operate for long periods, provide real-time data, and have extensive application potential. These sensors communicate with sinks or with each other through wireless connections. Thus, energy efficiency and reliability are crucial in WSN designs.
Extending network lifetime is crucial in WSNs as they are used for uninterrupted, long-term data collection in remote or hard-to-reach areas where replacing sensor batteries in several sensors is unfeasible. Network functionality loss due to connection interruptions and reduced coverage can occur when energy is not used efficiently in these networks.
Thus, the extension of network lifetime can be achieved through the even distribution of energy consumption among sensors. Researchers emphasize combinations of four key design issues, including the Data Routing Problem (DRP), the Sink Placement Problem (SPP), the Activity Scheduling Problem (ASP), and the Coverage Problem (CP), to prolong network lifetime and conserve energy in WSNs.
The integration of various design elements can potentially increase network lifetime. The decisions that optimize the reliability and lifetime of the network are interrelated in the most efficient WSN design. Thus, addressing them in a unified framework can be an effective strategy.
Existing studies mostly focus on a subset of four design problems or a single decision type to enhance network lifetime. In the literature, a holistic approach integrating all key design problems and network reliability in the same model is missing.
The Proposed Integrated Approaches
In this study, researchers addressed network reliability and all design problems in an integrated manner. They proposed strategies like Double Copy (DC) for multi-copy transmission, Single Copy (SC) for single-path data transmission, and a Hybrid (H) approach where copying happens in sensors transmitting to central nodes to jointly address key WSN design issues and network reliability.
Researchers created mixed-integer mathematical models for the proposed strategies. The network reliability of the proposed strategies was measured by generating various scenarios. Finally, researchers developed a heuristic method to design large-scale, reliable, and long-lifetime networks effectively.
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The Design Problems
DRP ensures optimal data-flow paths from sensors to sinks or to other sensors. Energy efficiency is critical in identifying these paths. Scheduling achieved using ASP is crucial for maintaining a balanced energy consumption distribution among sensors and ensuring the network's longevity and continuous operation.
The sink locations are determined by SPP to which sensor information will be sent, and data transmission paths are established to these locations. The sink location directly impacts the data transmission paths and thus, the sensors' energy consumption.
Areas of interest are monitored by addressing CP through sensor placement in particular areas. Coverage levels vary by area, with some areas more important than others. Additionally, other important factors are also considered, including scalability, cost, security, fault tolerance, energy efficiency, reliability, and connectivity.
The Strategies
The SC strategy maximizes network lifetime by transmitting data along minimum-cost paths. However, it does not ensure reliability, as node or link failures can interrupt communication. The DC strategy enhances reliability by sending multiple copies of data through primary and secondary paths, ensuring continuous transmission even during failures, though it increases energy consumption.
To address this trade-off, the H strategy was introduced. It combines the energy efficiency of SC with the reliability of DC by selectively copying data rather than at every sensor. In this approach, only the sensors transmitting data to central nodes copy the data.
Here, the central node is the sensor in the network with high data density and is vulnerable to damage. This selective copying could improve fault tolerance while conserving energy, achieving a balance between extended network lifetime and reliable data transmission.
Key Findings and Future Outlook
Researchers evaluated three strategies for WSNs under different scenarios. The SC strategy performed best in maximizing network lifetime, while the DC strategy achieved superior reliability through redundant data transmission. The H strategy effectively provided a balanced trade-off between lifetime and reliability by combining the strengths of both approaches.
To efficiently solve large-scale instances of the H strategy, a Lagrangian Heuristic (LH) method was employed. This approach used a Dantzig–Wolfe column generation technique for the Lagrangian subproblem and constructed feasible solutions iteratively, with performance validated against the Gurobi solver.
Future research must compare these strategies with new reliability-focused methods, incorporate probabilistic sensor detection ranges, and integrate explicit reliability constraints or variables into the network design model.
In conclusion, the findings of the study significantly contributed to the literature by integrating all four key problems to realize long network lifetimes in WSNs.
Journal Reference
Çelik, E., & Keskin, M. E. (2026). Wireless sensor network design with reliable and long network lifetime. Scientific Reports, 16(1), 12458. DOI: 10.1038/s41598-026-46014-x, https://www.nature.com/articles/s41598-026-46014-x
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