Images/videos are often uploaded in situations like disasters. This can tax the network in terms of increased load and thereby upload latency, and this can be critical for response activities. In such scenarios, prior work has shown that there is significant redundancy in the content (e.g., similar photos taken by users) transferred. By intelligently suppressing/deferring transfers of redundant content, the load can be significantly reduced, thereby facilitating the timely delivery of unique, possibly critical information. A key challenge here however, is detecting 'what content is similar,' given that the content is generated by uncoordinated user devices. Towards addressing this challenge, we propose a framework, wherein a service to which the content is to be uploaded first solicits metadata (e.g, image features) from any device uploading content. By intelligently comparing this metadata with that associated with previously uploaded content, the service effectively identifies (and thus enables the suppression of) redundant content. Our evaluations on a testbed of 20 Android smartphones and via ns3 simulations show that we can identify similar content with a 70% true positive rate and a 1% false positive rate. The resulting reduction in redundant content transfers translates to a latency reduction of 44 % for unique content.
Fuel cell electric vehicles (FCEVs), which use polymer electrolyte membrane fuel cells (PEMFCs), provide a prospect to add to a future of harmful-emission-free mobility. However, an in-depth understanding of degradation mechanisms and contributions to performance losses is needed to commercialize FCEVs further. Most previous PEMFC degradation research has focused on global indicators of the cell condition. Still, failure occurs typically due to inhomogeneities in production or operation, leading to localized regions of high degradation rates. Despite simulations indicating that local degradation effects are significantly more pronounced at larger scales, experimental studies only exist for small-sized laboratory fuel cells so far. Here, we present the results of a comprehensive study of spatial distributions of essential PEMFC parameters using electrochemical impedance spectroscopy across the cell surface of automotive-size fuel cells with an active area of 285 cm 2 . In particular, the results reveal increasing mass transport problems with increasing distance from the air inlet and a tendency of lower proton resistances in the center of the cell. One hundred twenty realistic freeze-start cycles degenerated the cell performance drastically. The outer cell regions, subject to the lowest temperatures, showed the most substantial degradation rates, partly compensated by central cell regions with slightly higher temperatures. These findings bridge the gap between simulation and experiment and provide valuable insights for future fuel cell design and operating strategies.
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