NeTS-NOSS: Collaborative Research: LEAPNet: Self-adaptable All Terrain Sensor Networks

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In deployment of sensor networks for various applications, sensors need to be placed in the areas of difficult terrain and natural obstacles. In such settings, many existing algorithms may perform poorly or may have high overhead while inefficiently consuming energy. One approach is to utilize mobile sensors in these situations, such as sensors with wheels. However, mobile wheeled sensors may not be able to move to the desired locations in the areas of difficult terrain with obstacles. Wheeled sensors can also be very expensive. A hopping sensor is a type of mobile sensor with a bionic mobility design that is inspired by creatures, such as grasshoppers. These sensors are still at an interesting concept stage. This proposal addresses the design, prototyping, and evaluation of hopping sensors and efficient algorithms for sensor deployment in difficult areas and rugged terrain. We focus on four research issues that are critical to the effective deployment and management of large scale sensor networks in such settings: robust and power-efficient hopping sensors, sensor localization, sensor coverage, and deployment of a self-adaptive all terrain sensor networks equipped with the hopping sensors and the proposed algorithms, which is called LEAPNet. Most future sensor networks are likely to be deployed in our targeted environments, and hence this research will benefit real-world applications such as monitoring ecosystems, disaster relief, and military reconnaissance. Strong collaborative efforts will be made to provide efficient and practical solutions with solid engineering designs and strong algorithmic foundations for this purpose. In addition, an innovative integration of the proposed research and education program will provide students with analytical skills and hands-on experiences by emerging technologies, which will better prepare them for strong technical careers in this rapidly growing and changing area.