A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) are considered producers of large amounts of rich data. Four types of data-driven models that correspond with various applications are identified as WSNs: query-driven, event-driven, time-driven, and hybrid-driven. The aim of the classification of data-driven models is to get real-time applications of specific data. Many challenges occur during data collection. Therefore, the main objective of these data-driven models is to save the WSN’s energy for processing and functioning during the data collection of any application. In this survey article, the recent advancement of data-driven models and application types for WSNs is presented in detail. Each type of WSN is elaborated with the help of its routing protocols, related applications, and issues. Furthermore, each data model is described in detail according to current studies. The open issues of each data model are highlighted with their challenges in order to encourage and give directions for further recommendation.

SZ-GESA

In this article, advanced tools are provided to steppe specialists to guide them in choosing the integrated development policies for steppe and pastoral zones. To this end, the use of adapted mobile wireless sensor networks (WSN) is proposed. Thus, a distributed and localized protocol dealing with the self-deployment problem resulting from mobile sensor random deployment is presented, on a steppe rangeland. This scheme entirely based on a geometric approach dealing with geodesy and steppe zones characteristics, allows mobile sensors moving to optimal positions on these study rangelands. The Geodesic Efficient Self-Deployment Algorithm in Steppe Zones (sz-GESA), so called, in its approach to solve the self-deployment problem for a given geographical rangelands type, showed during simulations a great robustness for the WSN adapted to this kind of zones by allowing optimization of the coverage and to idealize the connectivity. Obtained results are very encouraging and let us think for more research enhancing this developed system more efficiently.