Supporting the Specification and Runtime Validation of Asynchronous Calling Patterns in Reactive Systems

Wireless sensor networks (“sensornets”) are highly distributed and concurrent, with program actions bound to external stimuli. They exemplify a system class known as reactive systems, which comprise execution units that have “hidden” layers of control flow. A key obstacle in enabling reactive system developers to rigorously validate their implementations has been the absence of precise software component specifications and tools to assist in leveraging those specifications at runtime. We address this obstacle in three ways: (i) We describe a specification approach tailored for reactive environments and demonstrate its application in the context of sensornets. (ii) We describe the design and implementation of extensions to the popular nesC tool-chain that enable the expression of these specifications and automate the generation of runtime monitors that signal violations, if any. (iii) Finally, we apply the specification approach to a significant collection of the most commonly used software components in the TinyOS distribution and analyze the overhead involved in monitoring their correctness

Polymers: Opening Door to Future Batteries

Research of post lithium ion batteries is attracting considerable attention. While there have been significant advancements in understanding the challenges of Li-O2 and Li-S, the development of gas separation and ion selective membranes will be crucial in their commercialization due to their potential to separate O2 from air and impeding polysulfide dissolution while permitting rapid diffusion of lithium ions. In addition, research of novel and highly conductive and selective polymer electrolytes will be essential in overcoming the challenges of liquid based electrolytes in both the air and sulfur based battery systems

Group-wise performance evaluation of processor co-allocation in multi-cluster systems

Abstract. Performance evaluation in multi-cluster processor co-allocation- like in many other parallel job scheduling problems- is mostly done by computing the average metric value for the entire job stream. This does not give a comprehensive understanding of the relative performance of the different jobs grouped by their characteristics. It is however the characteristics that affect how easy/hard jobs are to schedule. We, therefore, do not get to understand scheduler performance at job type level. In this paper, we study the performance of multi-cluster processor co-allocation for different job groups grouped by their size, components and widest component. We study their relative performance, sensitivity to parameters and how their performance is affected by the heuristics used to break them up into components. We show that the widest component us characteristic that most affects job schedulability. We also show that to get better performance, jobs should be broken up in such a way that the width of the widest component is minimized

Parallel job scheduling - a status report

The popularity of research on the scheduling of parallel jobs demands a periodic review of the status of the field. Indeed, several surveys have been written on this topic in the context of parallel supercomputers [17, 20]. The purpose of the present paper is to update that material, and to extend it to include wor