Simulation-driven emulation of collaborative algorithms to assess their requirements for a large-scale WSN implementation

Assessing how the performance of a decentralized wireless sensor network (WSN) algorithm's implementation scales, in terms of communication and energy costs, as the network size increases is an essential requirement before its field deployment. Simulations are commonly used for this purpose, especially for large-scale environmental monitoring applications. However, it is difficult to evaluate energy consumption, processing and memory requirements before the algorithm is really ported to a real WSN platform. We propose a method for emulating the operation of collaborative algorithms in large-scale WSNs by re-using a small number of available real sensor nodes. We demonstrate the potential of the proposed simulation-driven WSN emulation approach by using it to estimate how communication and energy costs scale with the network’s size when implementing a collaborative algorithm we developed in for tracking the spatiotemporal evolution of a progressing environmental hazard

Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions

The development of pervasive communication devices and the emergence of the Internet of Things (IoT) have acted as an essential part in the feasibility of smart city initiatives. Wireless sensor network (WSN) as a key enabling technology in IoT offers the potential for cities to get smatter. WSNs gained tremendous attention during the recent years because of their rising number of applications that enables remote monitoring and tracking in smart cities. One of the most exciting applications of WSNs in smart cities is detection, monitoring, and tracking which is referred to as object tracking sensor networks (OTSN). The adaptation of OTSN into urban cities brought new exciting challenges for reaching the goal of future smart cities. Such challenges focus primarily on problems related to active monitoring and tracking in smart cities. In this paper, we present the essential characteristics of OTSN, monitoring and tracking application used with the content of smart city. Moreover, we discussed the taxonomy of OTSN along with analysis and comparison. Furthermore, research challenges are investigated concerning energy reservation, object detection, object speed, accuracy in tracking, sensor node collaboration, data aggregation and object recovery position estimation. This review can serve as a benchmark for researchers for future development of smart cities in the context of OTSN. Lastly, we provide future research direction