UC San Diego

Following the remarkable developments in computing and wireless communication technologies, there has been a rapid proliferation of mobile and embedded computing systems and applications that are becoming ubiquitous in all aspects of modern life, including the enterprise world, the entertainment world as well as in common household appliances. However, designers of new generations of these systems have to address a twofold demand for increasing application functionality as well as a reduction in device footprints. This dissertation proposes a design principle that can allow mobile computing applications to transcend the limitations on the end-devices, by splitting up the functionality of the application end points between the low-footprint wireless end-nodes and shared fixed nodes inside the network. It presents two instantiations of this idea in different types of wireless networks, identifying and solving some of the key challenges faced when applying the proposed principle. In the first part, the focus is on wireless access networks, where shared processing resources within the network can be used to support high- end applications on thin handheld clients. A major challenge here is to determine how to schedule the wireless communication and computing resources together to support a large set of clients. The second part of the dissertation demonstrates how the same design principle can be applied to wireless sensor networks to enable the use of simple, ultra-low-power sensor nodes. The resource limitations on the sensor nodes make it challenging to ensure the reliability of the sensor data, and a novel solution is proposed that leverages the correlation properties of the data to do so. The experimental results presented demonstrate the viability of the proposed architectural principle in systems that vary markedly in terms of application goals and device capabilities. It is shown that the technique proposed in the first part can achieve very efficient scheduling performance with minimal processing overheads. This enables the expansion of the application functionality without increasing the footprint of the end-devices. Similarly, in sensor networks, the error correction method demonstrated the feasibility of achieving the primary functionality, i.e., reliable data collection even when the footprints of the sensor nodes are reduced too far to implement traditional reliability measures. The techniques described will facilitate the adoption of infrastructure-based approach to system design, leading to high-end applications using low-footprint devices