Energy-Efficient Wireless Hopping Sensor Relocation Based on Prediction of Terrain Conditions

It is inevitable for data collection that IoT sensors are distributed to interested areas. However, not only the proper placement of sensors, but also the replacement of sensors that have run out of energy is very difficult. As a remedy, wireless charging systems for IoT sensors have been researched recently, but it is apparent that the availability of charging system is limited especially for IoT sensors scattered in rugged terrain. Thus, it is important that the sensor relocation models to recover sensing holes employ energy-efficient scheme. While there are various methods in the mobile model of wireless sensors, well-known wheel-based movements in rough areas are hard to achieve. Thus, research is ongoing in various areas of the hopping mobile model in which wireless sensors jump. Many past studies about hopping sensor relocation assume that all sensor nodes are aware of entire network information throughout the network. These assumptions do not fit well to the actual environment, and they are nothing but classical theoretical research. In addition, the physical environment (sand, mud, etc.) of the area in which the sensor is deployed can change from time to time. In this paper, we overcome the theoretical-based problems of the past researches and propose a new realistic hopping sensor relocation protocol considering terrain conditions. Since the status of obstacles around the sensing hole is unknown, the success rate of the hopping sensor relocation is used to predict the condition of the surrounding environment. Also, we are confident that our team is uniquely implementing OMNeT++ (Objective Modular Network Testbed in C++) simulation in the hopping sensor relocation protocol to reflect the actual communication environment. Simulations have been performed on various obstacles for performance evaluation and analysis, and we are confident that better energy efficiency with later appearance of sensing holes can be achieved compared to well-known relocation protocols.

Energy and Distance-Aware Hopping Sensor Relocation for Wireless Sensor Networks

Recent advances in big data technology collecting and analyzing large amounts of valuable data have attracted a lot of attention. When the information in non-reachable areas is required, IoT wireless sensor network technologies have to be applied. Sensors fundamentally have energy limitations, and it is almost impossible to replace energy-depleted sensors that have been deployed in an inaccessible region. Therefore, moving healthy sensors into the sensing hole will recover the faulty sensor area. In rough surfaces, hopping sensors would be more appropriate than wheel-driven mobile sensors. Sensor relocation algorithms to recover sensing holes have been researched variously in the past. However, the majority of studies to date have been inadequate in reality, since they are nothing but theoretical studies which assume that all the topology in the network is known and then computes the shortest path based on the nonrealistic backing up knowledge—The topology information. In this paper, we first propose a distributed hopping sensor relocation protocol. The possibility of movement of the hopping sensor is also considered to recover sensing holes and is not limited to applying the shortest path strategy. Finally, a performance analysis using OMNeT++ has demonstrated the solidification of the excellence of the proposed protocol.