POWDER is a highly flexible, deeply programmable, and city-scale scientific instrument that enables cutting-edge research in wireless technologies. Researchers interact with the POWDER platform via the Internet to conduct their experiments, with zero penalty for remote access. In this two-part demonstration, the POWDER implementers show how to use the platform. First, they present the workflow that researchers follow to conduct experiments. Second, they highlight some of the hardware and software building blocks available through POWDER, including components related to over-the-air wireless and mobile networking, 5G, and massive MIMO.

Fail-slow hardware is an under-studied failure mode. We present a study of 114 reports of fail-slow hardware incidents, collected from large-scale cluster deployments in 14 institutions. We show that all hardware types such as disk, SSD, CPU, memory, and network components can exhibit performance faults. We made several important observations such as faults convert from one form to another, the cascading root causes and impacts can be long, and fail-slow faults can have varying symptoms. From this study, we make suggestions to vendors, operators, and systems designers.

We will demonstrate features and capabilities of the PhantomNet testbed. PhantomNet is a mobile testbed, at the University of Utah, aimed at enabling a broad range of mobile networking related research. PhantomNet is remotely accessible and open to the mobile networking research community.

No abstract available.

No abstract available.

An important correctness criterion for software running on embedded microcontrollers is stack safety : a guarantee that the call stack does not overflow. Our first contribution is a method for statically guaranteeing stack safety of interrupt-driven embedded software using an approach based on context-sensitive dataflow analysis of object code. We have implemented a prototype stack analysis tool that targets software for Atmel AVR microcontrollers and tested it on embedded applications compiled from up to 30,000 lines of C. We experimentally validate the accuracy of the tool, which runs in under 10 sec on the largest programs that we tested. The second contribution of this paper is the development of two novel ways to reduce stack memory requirements of embedded software.

We have developed a new way to look at real-time and embedded software: as a collection of execution environments created by a hierarchy of schedulers. Common schedulers include those than run interrupts, bottom-half handlers, threads, and events. We have created algorithms for deriving response times, scheduling overheads, and blocking terms for tasks in systems containing multiple execution environments. We have also created task scheduler logic, a formalism that permits checking systems for race conditions and other errors. Concurrency analysis of low-level software is challenging because there are typically several kinds of locks, such as thread mutexes and disabling interrupts, and groups of cooperating tasks may need to acquire some, all or none of the available types of locks to create correct software. Our high-level goal is to create systems that are evolvable: they are easier to modify in response to changing requirements than are systems created using traditional techniques. We have applied our approach to two case studies in evolving software for networked sensor nodes.