FACT -- Operation of the First G-APD Cherenkov Telescope

Since more than two years, the First G-APD Cherenkov Telescope (FACT) is operating successfully at the Canary Island of La Palma. Apart from its purpose to serve as a monitoring facility for the brightest TeV blazars, it was built as a major step to establish solid state photon counters as detectors in Cherenkov astronomy. The camera of the First G-APD Cherenkov Telesope comprises 1440 Geiger-mode avalanche photo diodes (G-APD aka. MPPC or SiPM) for photon detection. Since properties as the gain of G-APDs depend on temperature and the applied voltage, a real-time feedback system has been developed and implemented. To correct for the change introduced by temperature, several sensors have been placed close to the photon detectors. Their read out is used to calculate a corresponding voltage offset. In addition to temperature changes, changing current introduces a voltage drop in the supporting resistor network. To correct changes in the voltage drop introduced by varying photon flux from the night-sky background, the current is measured and the voltage drop calculated. To check the stability of the G-APD properties, dark count spectra with high statistics have been taken under different environmental conditions and been evaluated. The maximum data rate delivered by the camera is about 240 MB/s. The recorded data, which can exceed 1 TB in a moonless night, is compressed in real-time with a proprietary loss-less algorithm. The performance is better than gzip by almost a factor of two in compression ratio and speed. In total, two to three CPU cores are needed for data taking. In parallel, a quick-look analysis of the recently recorded data is executed on a second machine. Its result is publicly available within a few minutes after the data were taken. [...]Comment: 19th IEEE Real-Time Conference, Nara, Japan (2014

Adaptive Energy-aware Scheduling of Dynamic Event Analytics across Edge and Cloud Resources

The growing deployment of sensors as part of Internet of Things (IoT) is generating thousands of event streams. Complex Event Processing (CEP) queries offer a useful paradigm for rapid decision-making over such data sources. While often centralized in the Cloud, the deployment of capable edge devices on the field motivates the need for cooperative event analytics that span Edge and Cloud computing. Here, we identify a novel problem of query placement on edge and Cloud resources for dynamically arriving and departing analytic dataflows. We define this as an optimization problem to minimize the total makespan for all event analytics, while meeting energy and compute constraints of the resources. We propose 4 adaptive heuristics and 3 rebalancing strategies for such dynamic dataflows, and validate them using detailed simulations for 100 - 1000 edge devices and VMs. The results show that our heuristics offer O(seconds) planning time, give a valid and high quality solution in all cases, and reduce the number of query migrations. Furthermore, rebalance strategies when applied in these heuristics have significantly reduced the makespan by around 20 - 25%.Comment: 11 pages, 7 figure

Design and operational control of an AGV system

In this paper we first deal with the design and operational control of Automated Guided Vehicle (AGV) systems, starting from the literature on these topics. Three main issues emerge: track layout, the number of AGVs required and operational transportation control. An hierarchical queueing network approach to determine the number of AGVs is decribed. Also basic concepts are presented for the transportation control of both a job-shop and a flow-shop. Next we report on the results of a case study, in which track layout and transportation control are the main issues. Finally we suggest some topics for further research

Routines and representations at work - observing the architecture of conceptual design

routines, representations, artifacts, product development, workplace observation, evolutionary economics, chip manufacturing