Accurate, up-to-date maps of transient traffic and hazards are invaluable to drivers, city managers, and the emerging class of self-driving vehicles. We present LiveMap, a scalable, automated system for acquiring, curating, and disseminating detailed, continually-updated road conditions in a region. LiveMap leverages in-vehicle cameras, sensors, and processors to crowd-source hazard
VM handoff enables rapid and transparent placement changes to executing code in edge computing use cases where the safety and management attributes of VM encapsulation are important. This versatile primitive offers the functionality of classic live migration but is highly optimized for the edge. Over WAN bandwidths ranging from 5
An emerging class of interactive wearable cognitive assistance applications is poised to become one of the key demonstrators of edge computing infrastructure. In this paper, we design seven such applications and evaluate their performance in terms of latency across a range of edge computing configurations, mobile hardware, and wireless networks,
Computer vision based technologies have seen widespread adoption over the recent years. This use is not limited to the rapid adoption of facial recognition technology but extends to facial expression recognition, scene recognition and more. These developments raise privacy concerns and call for novel solutions to ensure adequate user awareness,
Situational awareness involves the timely acquisition of knowledge about real-world events, distillation of those events into higher-level conceptual constructs, and their synthesis into a coherent context-sensitive view. We explore how convergent trends in video sensing, crowd sourcing and edge computing can be harnessed to create a shared real-time information system
We present OpenFace, our new open-source face recognition system that approaches state-of-the-art accuracy. Integrating OpenFace with inter-frame tracking, we build RTFace, a mechanism for denaturing video streams that selectively blurs faces according to specified policies at full frame rates. This enables privacy management for live video analytics while providing a
As video cameras proliferate, the ability to scalably capture and search their data becomes important. Scalability is improved by performing video analytics on cloudlets at the edge of the Internet, and only shipping extracted index information and meta-data to the cloud. In this setting, we describe interactive data exploration (IDE)
Industry investment and research interest in edge computing, in which computing and storage nodes are placed at the Internet's edge in close proximity to mobile devices or sensors, have grown dramatically in recent years. This emerging technology promises to deliver highly responsive cloud services for mobile computing, scalability and privacy-policy
The convergence of mobile computing and cloud computing enables new mobile applications that are both resource-intensive and interactive. For these applications, end-to-end network bandwidth and latency matter greatly when cloud resources are used to augment the computational power and battery life of a mobile device. This dissertation designs and implements
Computational offloading services at the edge of the Internet for mobile devices are becoming a reality. Using a wide range of mobile applications, we explore how such infrastructure improves latency and energy consumption relative to the cloud. We present experimental results from WiFi and 4G LTE networks that confirm substantial
Cyber-foraging is a technique to enable mobile devices to extend their computing power and storage by offloading computation or data to more powerful servers located in the cloud, or to proximate servers called surrogates. There are two main forms of cyber-foraging. One is computation offload, which is the offload of
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