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Augmented Reality (AR) applications can enable geographically distant users to collaborate using shared video feeds or interactive 3D holograms, and may be particularly useful in the socially distant context of the Covid-19 pandemic. However, a good user experience is key for their success and could be negatively impacted by network impairments, which are an inevitable occurrence in today's best-effort Internet. In this paper, we present the findings of an empirical user study, aimed at understanding the effects of network outages, on user experience and behavior, in a collaborative AR task. We highlight how network outages affected users in different ways depending on their role in the collaborative task, and how giving users explicit information about poor network conditions helped them deal with some of these negative effects. Furthermore, we report the strategies that users themselves adopted, to deal with outages, such as batching instructions, or shifting to a different spatial referencing style when communicating with their partners. Lastly, based on our findings, we present some design implications for future remote-collaborative AR applications. 

We revisit the long-standing problem of providing network QoS to applications, and propose the concept of judicious QoS -- combining the cheaper, best effort IP service with the cloud, which offers a highly reliable infrastructure and the ability to add in-network services, albeit at higher cost. Our proposed J-QoS framework offers a range of reliability services with different cost vs. delay trade-offs, including: i) a forwarding service that forwards packets over the cloud overlay, ii) a caching service, which stores packets inside the cloud and allows them to be pulled in case of packet loss or disruption on the Internet, and iii) a novel coding service that provides the least expensive packet recovery option by combining packets of multiple application streams and sending a small number of coded packets across the more expensive cloud paths. We demonstrate the feasibility of these services using measurements from RIPE Atlas and a live deployment on PlanetLab. We also consider case studies on how J-QoS works with services up and down the network stack, including Skype video conferencing, TCP-based web transfers and cellular access networks.