Book Description

The emergence of the technology of Wireless Sensor Networks (WSNs) has lead to m any changes in current and traditional computational techniques in order to adap t to their harsh and scarce requirements. A WSN consists of sensor nodes with wi reless communication abilities that allow them to form a network. As a network t hese sensor nodes are able to monitor and gather data about the environment. Act ions are then taken depending on the gathered data, forming a cheap way of doing previously expensive tasks. However the small capacities of these nodes introdu ce several limitations. Traditional operating systems for instance do not take i nto consideration the limitations in space and energy of WNSs and thus cannot be used. New system architectures have emerged to overcome these limitations. Each architecture follows one of the two traditional design concepts, event-driven o r thread-driven design. Although event-driven systems were assumed to generally perform better for embedded systems, tests have shown that event-driven systems tend to save more energy and space, while the thread-driven systems provide more concurrency and predictability, hence creating a tradeoff depending on the requ irements of the application at hand. Performance analyzers are often used to accurately measure the performance of a certain system when such a tradeoff is evident. Performance analyzers can also l ocate deficiencies and bottlenecks in a certain system for future improvements. The ever increasing complexity of applications executed by WSNs and the evolving nature of the underlying Embedded Operating Systems (EOSs) has led to the need for an accurate evaluation technique to guide practitioners in the field. This t hesis presents a novel approach towards providing a benchmarking and performance evaluation tool for comparing and analyzing the performance of WSN EOSs.