On Maximizing the Efficiency of Multipurpose WSNs Through Avoidance of Over- or Under-Provisioning of Information

A wireless sensor network (WSN) is a distributed collection of sensor nodes, which are resource constrained and capable of operating with minimal user attendance. The core function of a WSN is to sample physical phenomena and their environment and transport the information of interest, such as current status or events, as required by the application. Furthermore, the operating conditions and/or user requirements of WSNs are often desired to be evolvable, either driven by changes of the monitored phenomena or by the properties of the WSN itself. Consequently, a key objective for setting up/configuring WSNs is to provide the desired information subject to user defined quality requirements (accuracy, reliability, timeliness etc.), while considering their evolvability at the same time. The current state of the art only addresses the functional blocks of sampling and information transport in isolation. The approaches indeed assume the respective other block to be perfect in maintaining the highest possible information contribution. In addition, some of the approaches just concentrate on a few information attributes such as accuracy and ignore other attributes (e.g., reliability, timeliness, etc.). The existing research targeting these blocks usually tries to enhance the information quality requirements (accuracy, reliability, timeliness etc.), regardless of user requirements and use more resources, leading to faster energy depletion. However, we argue that it is not always necessary to provide the highest possible information quality. In fact, it is essential to avoid under or over provision of information in order to save valuable resources such as energy while just satisfying user evolvable requirements. More precisely, we show the interdependence of the different user requirements and how to co-design them in order to tune the level of provisioning. To discern the fundamental issues dictating the tunable co-design in WSNs, this thesis models and co-designs the sampling accuracy, information transport reliability and timeliness, and compares existing techniques. We highlight the key problems of existing techniques and provide solutions to achieve desired application requirements without under or over provisioning of information. Our first research direction is to provide tunable information transport. We show that it is possible to drastically improve efficiency, while satisfying the user evolvable requirements on reliability and timeliness. In this regard, we provide a novel timeliness model and show the tradeoff between the reliability and timeliness. In addition, we show that the reliability and timeliness can work in composition for maximizing efficiency in information transport. Second, we consider the sampling and information transport co-design by just considering the attributes spatial accuracy and transport reliability. We provide a mathematical model in this regard and then show the optimization of sampling and information transport co-design. The approach is based on optimally choosing the number of samples in order to minimize the number of retransmission in the information transport while maintaining the required reliability. Third, we consider representing the physical phenomena accurately and optimize the network performance. Therefore, we jointly model accuracy, reliability and timeliness, and then derive the optimal combination of sampling and information transport. We provide an optimized model to choose the right representative sensor nodes to describe the phenomena and highlight the tunable co-design of sampling and information transport by avoiding over or under provision of information. Our simulation and experimental results show that the proposed tunable co-design supports evolving user requirements, copes with dynamic network properties and outperforms the state of the art solutions