Since 2010, the Cal Poly Computer Science Department has required computing majors to select from a variety of CS0 courses to start their academic year. The broad objective of the course is to attract and retain undergraduates that have no prior experience in CS by using authentic problems that demonstrate the relevance and highlight the role of computers in solving "real world" problems. The course is offered in a variety of thematic "flavors" that leverage a student's pre-existing interests (e.g. in music or art), but all share the common goals of introducing students to the basics of programming, teamwork, and college-level study. While there is overlap in overall goals, the courses vary drastically in topic matter (e.g. robotics, gaming, music, computational art, mobile apps, security) and in pedagogical approach (e.g. principles of design, project-based student driven learning, and traditional topic-based programming modules). The introduction of this CS0 course has increased students' commitment to their major and success in follow-on classes. We present these successes and show that student GPAs in a follow-on object oriented programming course do not vary significantly for the differing subtopics and teaching pedagogies employed in the various flavors. Our report includes examining two student subgroups (those experienced with programming and those new to programming). Our evaluations suggest that the existence and goal of the course matter more than the specific content, with all subtopics and pedagogical approaches performing well.

The Intelligent Payload Experiment (IPEX) is a CubeSat mission to flight validate technologies for onboard instrument processing and autonomous operations for NASA's Earth Science Technologies Office (ESTO). Specifically IPEX is to demonstrate onboard instrument processing and product generation technologies for the Intelligent Payload Module (IPM) of the proposed Hyperspectral Infra-red Imager (HyspIRI) mission concept. Many proposed future missions, including HyspIRI, are slated to produce enormous volumes of data requiring either significant communication advancements or data reduction techniques. IPEX demonstrates several technologies for onboard data reduction, such as computer vision, image analysis, image processing and in general demonstrates general operations autonomy. We conclude this paper with a number of lessons learned through operations of this technology demonstration mission on a novel platform for NASA.

The combination of unlicensed spectrum, cheap wireless interfaces and the inherent convenience of untethered computing have made 802.11 based networks ubiquitous in the enterprise. Modern universities, corporate campuses and government offices routinely de-ploy scores of access points to blanket their sites with wireless Internet access. However, while the fine-grained behavior of the 802.11 protocol itself has been well studied, our understanding of how large 802.11 networks behave in their full empirical complex-ity is surprisingly limited. In this paper, we present a system called Jigsaw that uses multiple monitors to provide a single unified view of all physical, link, network and transport-layer activity on an 802.11 network. To drive this analysis, we have deployed an infrastructure of over 150 radio monitors that simultaneously capture all 802.11b and 802.11g activity in a large university building (1M+ cubic feet). We describe the challenges posed by both the scale and ambiguity inherent in such an architecture, and explain the algorithms and inference techniques we developed to address them. Finally, using a 24-hour distributed trace containing more than 1.5 billion events, we use Jigsaw's global cross-layer viewpoint to isolate performance artifacts, both explicit, such as management inefficiencies, and implicit, such as co-channel interference. We believe this is the first analysis combining this scale and level of detail for a production 802.11 network.

The Internet architecture provides an unsequenced datagram delivery service. Nevertheless, many higher-layer protocols, such as TCP, assume that packets are usually delivered in sequence, and consequently suffer significant degradation when packets are reordered in flight. While there have been several recent proposals to create protocols that adapt to reordering, evaluating their effectiveness requires understanding the dynamics of the reordering processes prevalent in the Internet. Unfortunately, Internet packet sequencing is a poorly characterized and understudied behavior. This failing can be largely attributed to the lack of accurate and universally applicable methods for measuring packet reordering. In this paper, we describe a new set of active measurement techniques that can reliably estimate one-way end-to-end reordering rates to and from arbitrary TCP-based servers. We validate these tools in a controlled setting and show how they can be used to measure the time-domain distribution of the reordering process along a given path.