| Description |
We are seeing an extensive proliferation of wireless devices including various types and forms of sensor nodes that are increasingly becoming ingrained in our daily lives. There has been a significant growth in wireless devices capabilities as well. This proliferation and rapid growth of wireless devices and their capabilities has led to the development of many distributed sensing and computing applications. In this dissertation, we propose and evaluate novel, efficient approaches for localization and computation offloading that harness distributed sensing and computing in wireless networks. In a significant part of this dissertation, we exploit distributed sensing to create efficient localization applications. First, using the sensing power of a set of Radio frequency (RF) sensors, we propose energy efficient approaches for target tracking application. Second, leveraging the sensing power of a distributed set of existing wireless devices, e.g., smartphones, internet-of-things devices, laptops, and modems, etc., we propose a novel approach to locate spectrum offenders. Third, we build efficient sampling approaches to select mobile sensing devices required for spectrum offenders localization. We also enhance our sampling approaches to take into account selfish behaviors of mobile devices. Finally, we investigate an attack on location privacy where the location of people moving inside a private area can be inferred using the radio characteristics of wireless links that are leaked by legitimate transmitters deployed inside the private area, and develop the first solution to mitigate this attack. While we focus on harnessing distributed sensing for localization in a big part of this dissertation, in the remaining part of this dissertation, we harness the computing power of nearby wireless devices for a computation offloading application. Specially, we propose a multidimensional auction for allocating the tasks of a job among nearby mobile devices based on their computational capabilities and also the cost of computation at these devices with the goal of reducing the overall job completion time and being beneficial to all the parties involved. |
