A comparison of software platforms for Wireless Sensor Networks: MANTIS, TinyOS and ZigBee

Wireless sensor networks are characterized by very tight code size and power constraints, and by a lack of well-established standard software development platforms such as Posix. In this paper, we present a comparative study between a few fairly different such platforms, namely MANTIS, TinyOS and ZigBee, when considering them from the application developer's perspective, i.e. by focusing mostly on functional aspects, rather than on performance or code size. In other words, we compare both the tasking model used by these platforms and the API libraries they offer. Sensor network applications are basically event based, so most of the software platforms are also built on considering event handling mechanism, however some use a more traditional thread based model. In this paper, we consider implementations of a simple generic application in MAN- TIS, TinyOS and the Ember ZigBee development framework, with the goal of depicting major differences between these platforms, and suggesting a programming style aimed at maximizing portability between them

Automatic Application-Specific Customization of Softcore Processor Microarchitecture, Masters Thesis, May 2006

Applications for constrained embedded systems are subject to strict runtime and resource utilization bounds. With soft core processors, application developers can customize the processor for their application, constrained by available hardware resources but aimed at high application performance. The more reconfigurable the processor is, the more options the application developers will have for customization and hence increased potential for improving application performance. However, such customization entails developing in-depth familiarity with all the parameters, in order to configure them effectively. This is typically infeasible, given the tight time-to-market pressure on the developers. Alternatively, developers could explore all possible configurations, but being exponential, this is infeasible even given only tens of parameters. This thesis presents an approach based on an assumption of parameter independence, for automatic microarchitecture customization. This approach is linear with the number of parameter values and hence, feasible and scalable. For the dimensions that we customize, namely application runtime and hardware resources, we formulate their costs as a constrained binary integer nonlinear optimization program. Though the results are not guaranteed to be optimal, we find they are near-optimal in practice. Our technique itself is general and can be applied to other design-space exploration problems