Traffic congestion, high gas price and inadequate public transportation are major challenges for any country, business or individual. The traditional approach to solving these problems has been to improve public transportation and use greener energy. These approaches require huge investment, research and time, and can only be carried out by governments or businesses. An alternative solution seeks to reduce the number of vehicles on the road based on ridesharing. Nevertheless, ridesharing is not a popular form of public transportation.In this paper, we summarize the results of a rideshare needs assessment survey conducted within the [university] community. The purpose behind this study was to understand commuter travel patterns, their needs and to identify their preferences for private vehicles and public transit for a variety of travel needs. Our results indicate that users are willing to increase participation in ridesharing programs if three core issues are addressed -trust, convenience and incentives.

Abstract. Optical circuit-switched networks such as National LambdaRail (NLR) offer dedicated bandwidth to support large-scale bulk data transfer. Though a dedicated circuit-switched network eliminates congestion from the network itself, it effectively "pushes" the congestion to the end hosts, resulting in lower-than-expected throughput. Previous approaches either use an ad-hoc proactive approach that does not generalize well or a sluggish reactive approach where the sending rate is only adapted based on synchronous feedback from the receiver. We address the shortcomings of such approaches using a two-step process. First, we improve the adaptivity of the reactive approach by proposing an asynchronous, fine-grained, rate-based approach. While this approach enhances performance, its limitation is that it is still reactive. Consequently, we then analyze the predictive patterns of load on the receiver and provide strong evidence that a proactive approach is not only possible, but also necessary, to achieve the best performance in dynamically varying end-host conditions.