Research has shown that Heterogeneous Sensor Networks (HSNs) can significantly improve the performance of sensor networks. To achieve better performance, we adopt an HSN model consisting of a small number of powerful high-end sensors (H-sensors) and a large number of low-end sensors (L-sensors). The objective of this project is to investigate innovative network architectures of HSNs, and develop energy-efficient, self-healing schemes and routing protocols for HSNs. We plan to build an integrated research and education program. The research components of the project consist of the following two parts: . Investigating efficient and robust network architectures of HSNs. We will investigate innovative network architectures for two different types of HSNs: HSNs where the locations of H-sensors are controllable and NOT controllable. We will determine the optimal density of H-sensors and L-sensors, and the optimal locations of H-sensors to minimize the cost of sensor nodes while ensuring a network lifetime and coverage requirement. We propose a novel Density-Varying-Deployment scheme for H-sensors. We will also design robust clustering schemes that can tolerate H-sensor failures and provide reliable network structures. . Designing self-healing and energy-efficient schemes and routing protocols for HSNs. The primary functionality of wireless sensor networks is to sense the environment and transmit the acquired information to a base station for further processing. Thus, routing is an essential operation in sensor networks. Typical sensor nodes are small, unreliable devices with limited energy supply. The routing protocols should be energy-efficient and robust to sensor failures, and be able to find new paths when nodes fail. By utilizing powerful H-sensors, we will design self-healing, energy-efficient routing protocols for HSNs which take into consideration of data fusion. The research is tightly coupled with an educational program that includes the following four themes, 1) Mentoring graduate and undergraduate students, and recruiting students of underrepresented groups in North Dakota and Tennessee to participate in the project. 2) Developing a new graduate course-Wireless Sensor Networks. 3) Field study of sensor networks. Sensor networks have been deployed in several farms in North Dakota for agricultural monitoring and several chemical/nuclear plants in Tennessee for hazard monitoring. We will take students to the farms and plants to study how to improve the performance of these real sensor networks by applying our research results. 4) Integrating research and education together by setting up a Heterogeneous Sensor Network Lab. The Intellectual Merits include: 1) In this research, we will develop innovative network architectures for two different kinds of HSNs, i.e., the locations of H-sensors are controllable or not. 2) We will design energy-efficient and self-healing routing protocols for HSNs, which are robust to node failures and prolong network lifetime. The Broader Impacts are: Recruiting students of underrepresented groups, including female, low incoming, first generation, Native American, and African American students in North Dakota
