Abstract
Energy is one of the most important issues in wireless sensor networks, which are formed by a large number of wireless sensor nodes and used in a large number of applications such as healthcare, environment and agriculture, Internet of things (IoT), military, and industry. The nodes can be powered by primary batteries or by harvesting energy from the environment. Whatever the case, energy is a scare resource in the sensor nodes, so it must be wisely managed in order to keep the nodes alive and assure the correct performance of the network. This special issue presents four papers tackling with these topics.
In “Data transmission optimization algorithm for network utility maximization in wireless sensor networks,” authors proposed a joint scheme for rate control, scheduling, routing, and power control protocol for wireless sensor networks based on compressive sensing. Using a network utility maximization formulation, they present cross-layer optimization solutions using Lagrangian multipliers in the transport, network, media access control, and physical layers. Through simulation results, they demonstrate the performance in terms of stability of the error ratio of compressive sensing, energy consumption, and transmission delay in wireless sensor networks.
In “Guaranteed convergence control for consensus of mobile sensor networks with dynamical topologies,” authors propose a novel guaranteed convergence control algorithm to switch topologies of mobile sensors so that power consumption in the sensor network can be reduced as well as the mobile sensors reach consensus with guaranteed convergence.
In “Virtual movement of relay nodes for two-tier wireless sensor networks in tunnels,” authors proposed a new approach for the placement of relay nodes of two-tier wireless sensor networks in a tunnel environment in order to reduce the use of extra batteries and the number of forwarding times for a message. The approach makes fixed relay nodes work in turns to obtain the virtual movement of relay nodes. The approach provides a novel method that has been proved to find optimal places to deploy relay nodes in tunnel environments.
In “Energy-aware determination of compression for low latency in solar-powered wireless sensor Networks,” the surplus solar harvested energy is used to reduce the delay time for transmitting data between nodes of wireless sensor networks. Data size reduction increases network lifetime since the data transmission process takes up a large part of energy consumption. However, reducing data size results in increased delay time due to not only the compression computation time but also the waiting time to gather a sufficient amount of data for compression. In this paper, nodes with residual energy less than a given threshold transfer data with compression in order to reduce energy consumption, whereas nodes with residual energy over that threshold transfer data without compression to reduce the delay time using the surplus harvested energy. Simulation-based performance verifications show that the proposed technique exhibits optimal performance in terms of both energy and delay times compared with traditional methods.
We would like to thank all the authors for their valuable contributions to this Special Issue. We are indebted to the journal editors and all external reviewers for their huge work that helped the authors further enhance the quality of their manuscripts. It has been also an honor for us to serve as the guest editors for this Special Issue.