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--Wireless sensor networks have emerged recently as an effective way of monitoring remote or inhospitable physical environments. One of the major challenges in devising such networks lies in the constrained energy and computational resources available to sensor nodes. These constraints must be taken into account at all levels of system hierarchy.The deployment of sensor nodes is the first step in establishing a sensor network. Since sensor networks contain a large number of sensor nodes, the nodes must be deployed in clusters, where the location of each particular node cannot be fully guaranteed a priori. Therefore, the number of nodes that must be deployed in order to completely cover the whole monitored area is often higher than if a deterministic procedure were used. In networks with stochastically placed nodes, activating only the necessary number of sensor nodes at any particular moment can save energy. We introduce a heuristic that selects mutually exclusive sets of sensor nodes, where the members of each of those sets together completely cover the monitored area. The intervals of activity are the same for all sets, and only one of the sets is active at any time. The experimental results demonstrate that by using only a subset of sensor nodes at each moment, we achieve a significant energy savings while fully preserving coverage.

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Recently, several wireless sensor network studies demonstrated large discrepancies between experimentally observed communication properties and properties produced by widely used simulation models. Our first goal is to provide sound foundations for conclusions drawn from these studies by extracting relationships between location (e.g distance) and communication properties (e.g. reception rate) using non-parametric statistical techniques. The objective is to provide a probability density function that completely characterizes the relationship. Furthermore, we study individual link properties and their correlation with respect to common transmitters, receivers and geometrical location.The second objective is to develop a series of wireless network models that produce networks of arbitrary sizes with realistic properties. We use an iterative improvement-based optimization procedure to generate network instances that are statistically similar to empirically observed networks. We evaluate the accuracy of our conclusions using our models on a set of standard communication tasks, like connectivity maintenance and routing.

Abstract-The growing class of portable systems, such as personal computing and communication devices, has resulted in a new set of system design requirements, mainly characterized by dominant importance of power minimization and design reuse. The energy efficiency of systems-on-a-chip (SOC) could be much improved if one were to vary the supply voltage dynamically at run time. We develop the design methodology for the lowpower core-based real-time SOC based on dynamically variable voltage hardware. The key challenge is to develop effective scheduling techniques that treat voltage as a variable to be determined, in addition to the conventional task scheduling and allocation. Our synthesis technique also addresses the selection of the processor core and the determination of the instruction and data cache size and configuration so as to fully exploit dynamically variable voltage hardware, which results in significantly lower power consumption for a set of target applications than existing techniques. The highlight of the proposed approach is the nonpreemptive scheduling heuristic, which results in solutions very close to optimal ones for many test cases. The effectiveness of the approach is demonstrated on a variety of modern industrialstrength multimedia and communication applications. Index Terms-High-level synthesis, scheduling, synthesis for low power, system-on-a-chip (SOC).