Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

An Innovation System Perspective on Adaptation Strategies to Climate Variability and Water Management in India

Government policies play a critical role in influencing market conditions, institutions and overall agricultural productivity. The thesis therefore looks into the history of agriculture development in India. Taking a political economy perspective, the historical account looks at significant institutional and technological innovations carried out in pre- independent and post independent India. It further focuses on the Green Revolution in Asia, as forty years after; the agricultural community still faces the task of addressing recurrent issue of food security amidst emerging challenges, such as climate change. It examines the Green Revolution that took place in India during the late 1960s and 70s in a historical perspective, identifying two factors of institutional change and political leadership. Climate change in agriculture development has become a major concern to farmers, researchers and policy makers alike. However, there is little knowledge on the farmers’ perception to climate change and to the extent they coincide with actual climatic data. Using a qualitative approach,it looks into the perceptions of the farmers in four villages in the states of Maharashtra and Andhra Pradesh. While exploring the adaptation strategies, the chapter looks into the dynamics of who can afford a particular technology and who cannot and what leads to a particular adaptation decision thus determining the adaptive capacity in water management. The final section looks into the devolution of authority for natural resource management to local user groups through the Water Users’ Associations as an important approach to overcome the long-standing challenges of centralized state bureaucracies in India. It addresses the knowledge gap of why some local user groups are able to overcome governance challenges such as elite capture, while others-that work under the design principles developed by Elinor Ostrom. It draws conclusions on how local leadership, can be promoted to facilitate participatory irrigation management.