Technological advances in wireless sensor networks enabling diverse Internet of Things applications

Relevant technologies and standards related to wireless sensor networks (WSNs) have advanced over the past few years, and diverse Internet of Things (IoT) applications based on WSNs have already achieved some commercial success in applications such as smart parking and metering systems, ¹ smart farming system, environmental monitoring, and many other applications. As such, the rate of adoption of WSNs in diverse IoT applications from home appliances to industrial systems, both for replacing traditional wired sensor systems and for new automation systems, will be increasing rapidly in the coming years due to some clear advantages of lower cost, easier deployment, more flexibility, and especially due to more opportunities for intelligent distributed data processing and collaboration.

However, since diverse IoT applications such as consumer IoT and industrial IoT applications have different performance requirements in the aspects of fault tolerance, reliability, real-time characteristics, and robustness, the design approach and goals can be varied. In addition, the performance evaluation for such diverse applications is nontrivial, with diverse approaches, depending on the different application areas, ranging from mathematical analysis to statistical simulations to testbed analysis with different scales. ²

This special collection on technological advances in WSNs enabling diverse applications such as consumer IoT and industrial IoT focuses on the latest research and development, and adoption of WSNs in the perspective of the physical or medium access control (MAC) layer up to the application layer. The special collection has been organized to share the state-of-the-art research and developments in WSNs with a special emphasis given to the technical advances in Wireless Sensor Networks Enabling Diverse IoT Applications obtained within the last few years. Through the peer-review process supervised by the editorial office of International Journal of Distributed Sensor Networks, any conflict of interests has been avoided by an appropriate selection of a guest editor and at least three invited reviewers selection by the guest editor. Finally, five papers have been accepted among 12 submissions for publication in this special collection.

One paper provides the physical layer performance evaluation results on the LoRa low-power wide-area network technology enabling diverse range of IoT applications. ³ Another paper proposes an ultra low-power medium access control protocol, WideMAC, by analyzing the maximum relative clock drift characteristics in WSNs. ⁴ The next paper reports a new IoT system power control scheme based on an average-reward reinforcement learning algorithm for Quality-of-Service provision. ⁵ There are two papers relevant to the localization and the positioning systems. One paper proposes anchor-free localization algorithm to achieve high localization accuracy with flexible structure, low cost, and high stability, ⁶ while the other paper, ⁷ rather than focusing on indoor positioning accuracy, studied store layout optimization by linking the customers’ positioning data with the transaction data, rather than focusing on the indoor positioning accuracy. The following paragraphs summarize these papers in more detail.

The paper titled “Performance of a low-power wide-area network based on LoRa technology: Doppler robustness, scalability, and coverage” by Juha Petäjäjärvi, Konstantin Mikhaylov, Marko Pettissalo, Janne Janhunen, and Jari Iinatti provides an extensive performance evaluation results on LoRa wide-area network (LoRaWAN). It first overviews the LoRa technology in views of the physical layer, the link layer, and the network architecture and analyzes the scalability of the LoRaWAN. Then the paper presents extensive experimental results with a transmit power of 14 dBm and the spread spectrum factor of 12 on water and in mobile scenarios with Doppler shift. With low-speed mobility below 25 km/h, it shows a sufficient reliability for a variety of applications (e.g. human or animal-centric applications) requiring low mobility.

In “Ultra-low-power media access control protocol based on clock drift characteristics in wireless sensor networks” by Wooguil Pak, the source of uncertainty for synchronization protocols is analyzed through extensive measurements. By modeling the maximum relative clock drift based on the analyzed characteristics, the author proposes a WideMAC protocol supporting a wide range of duty cycles. In WideMAC, a transmitting node calculates the wakeup time of reception node by estimating the upper bound of total timing error. Empirical evaluation results show that WideMAC saves significant amount of energy through the accurate estimation of wakeup time.

In “R-learning-based team game model for Internet of things quality-of-service control scheme” by Sungwook Kim, the author proposes using R-learning algorithm and docitive paradigm to enable quality of service (QoS) in the IoT world. The docitive paradigm is used in concurrency with R-learning to share knowledge in a cooperative manner with other actors in an IoT system. This allows the development of a new distributed IoT system power control scheme for QoS that supports self-adaptability and real-time decision making.

The paper titled “A simple efficient anchor-free node localization algorithm for wireless sensor networks” by Tao Du, Shouning Qu, Qingbei Guo, and Lianjiang Zhu proposes an anchor-free ladder diffusion node localization algorithm (LDLA). In LDLA, every sensor node calculates its relative position with a sink node using the ladder diffusion method. The performance evaluations prove that LDLA achieves high localization accuracy like anchor-based algorithm as well as maintaining the advantages of anchor-free algorithms such as flexibility of deployment, and low computation and communication overheads.

While most of existing indoor positional algorithms focus on increasing the accuracy rate solely, the paper titled “Store layout optimization using indoor positioning system” by Hyunwoo Hwangbo, Jonghyuk Kim, Zoonky Lee, and Soyean Kim proposes the optimal store layout algorithm by linking indoor positioning data with customer transaction data. They conducted a real-world store experiment over 11 months and compared the positioning data and transaction data before and after store layout optimization decisions in order to identify which customer movement patterns generate the highest sales. The proposed system is also expected to provide diverse retail services such as real-time personalized offers, optimal allocation of staffs, and navigation services.