Over the past decades, wireless sensor networks (WSNs) have experienced exceptional growth, their success reflecting their continuously increasing areas of application (e.g., area monitoring, environmental sensing, threat detection, etc.). Besides, the integration of WSNs in the IoT allows the latter to penetrate deeply into our daily lives and provide various convenient services enabling users to access, use, and process information collected from sensors through smart devices.
On the one hand, WSN devices\' small size and low cost allow for development in large-scale environments. On the other hand, in the absence of infrastructure (due to their wireless nature), their operation depends on their limited batteries\' energy supply. As a result of the limitations deriving from the low-capacity batteries, the lifetime of a WSN is inextricably linked to them. Thus, the framework underlying the devices\' energy usage plays a vital role in the network\'s overall energy consumption and lifetime. For example, minimizing the number of packet transmissions among the WSN nodes or choosing a better location for the sink node can result in a lifetime extension.
Apart from optimizing the energy consumption, another way to increase a WSN\'s lifetime is to find an optimal way to recharge its nodes\' batteries. In these so-called Rechargeable Wireless Sensor Networks (RWSNs), a vehicle (e.g., an unmanned autonomous vehicle, a drone, etc.) able to recharge the nodes\' batteries is implemented and moves among the nodes replenishing their batteries. To take advantage of this procedure and maximize the lifetime of the RWSN and the recharging vehicle itself, a framework (or policy) on which the recharging vehicle bases its operation must be considered. This framework has to take into account issues such as the minimization of the distance travelled by the recharging vehicle to recharge the nodes, the optimization of the number of visited (for a replenishment) nodes, the minimization of the energy consumption of the vehicle, among others.
This Special Issue invites original research papers on new frameworks, algorithms, protocols, architectures, technologies, and solutions for extending the lifetime of a WSN (or RWSN). Relevant topics include, but are not limited to:
- Lifetime extension
- Energy consumption optimization
- Energy-efficient routing
- Load balancing
- Optimal location of WSN nodes
- Optimal location of sink node(s)
- Machine learning-based WSN techniques
- AI-enabled routing
- Optimal data collection
- Data reduction/compression
- Wireless energy transfer techniques
- Joint information and energy transfer
- Energy harvesting
- Recharging vehicles
- Simulation tools
- Physical layer challenges, issues, and solutions
- Mobile edge/fog computing
- Manuscript Submission Information
- Placeholder to add info for submission process, charge, etc.
Dr. Konstantinos Oikonomou
Dr. Constantinos Angelis
Dr. Georgios Tsoumanis