Abstract
Public spaces like concert stadiums and sporting arenas are ideal venues for AR content delivery to crowds of mobile phone users. Unfortunately, these environments tend to be some of the most challenging in terms of lighting and dynamic staging for vision-based relocalization. In this paper, we introduce FLASH1, a system for delivering AR content within challenging lighting environments that uses active tags (i.e., blinking) with detectable features from passive tags (quads) for marking regions of interest and determining pose. This combination allows the tags to be detectable from long distances with significantly less computational overhead per frame, making it possible to embed tags in existing video displays like large jumbotrons. To aid in pose acquisition, we implement a gravity-assisted pose solver that removes the ambiguous solutions that are often encountered when trying to localize using standard passive tags. We show that our technique outperforms similarly sized passive tags in terms of range by 20-30% and is fast enough to run at 30 FPS even within a mobile web browser on a smartphone.

Abstract
Virtual Reality (VR) telepresence platforms are being challenged to support live performances, sporting events, and conferences with thousands of users across seamless virtual worlds. Current systems have struggled to meet these demands which has led to high-profile performance events with groups of users isolated in parallel sessions. The core difference in scaling VR environments compared to classic 2D video content delivery comes from the dynamic peer-to-peer spatial dependence on communication. Users have many pair-wise interactions that grow and shrink as they explore spaces. In this paper, we discuss the challenges of VR scaling and present an architecture that supports hundreds of users with spatial audio and video in a single virtual environment. We leverage the property of spatial locality with two key optimizations: (1) a Quality of Service (QoS) scheme to prioritize audio and video traffic based on users' locality, and (2) a resource manager that allocates client connections across multiple servers based on user proximity within the virtual world. Through real-world deployments and extensive evaluations under real and simulated environments, we demonstrate the scalability of our platform while showing improved QoS compared with existing approaches.

Abstract
In this paper we describe how to integrate Internet protocols (TCP/IP) into a typical hierarchical master-slave fieldbus network, supporting a logical ring token passing mechanism between master stations. The integration of TCP/IP in the fieldbus protocol rises a number of issues that must be addressed properly. In this paper we particularly address the issues related to the conveyance of IP Datagrams in fieldbus frames (fragmentation/de-fragmentation) and on how to support the symmetry inherent to the TCP/IP protocols in fieldbus slaves, which lack communication initiative. Copyright (C) 2001 IFAC.

Abstract

Abstract
Consider a wireless sensor network (WSN) where a broadcast from a sensor node does not reach all sensor nodes in the network; such networks are often called multihop networks. Sensor nodes take individual sensor readings, however, in many cases, it is relevant to compute aggregated quantities of these readings. In fact, the minimum and maximum of all sensor readings at an instant are often interesting because they indicate abnormal behavior, for example if the maximum temperature is very high then it may be that a fire has broken out. In this context, we propose an algorithm for computing the min or max of sensor readings in a multihop network. This algorithm has the particularly interesting property of having a time complexity that does not depend on the number of sensor nodes; only the network diameter and the range of the value domain of sensor readings matter. © 2009 pringer Science+Business Media B.V.

Abstract
Managing the physical and compute infrastructure of a large data center is an embodiment of a Cyber-Physical System (CPS). The physical parameters of the data center (such as power, temperature, pressure, humidity) are tightly coupled with computations, even more so in upcoming data centers, where the location of workloads can vary substantially due, for example, to workloads being moved in a cloud infrastructure hosted in the data center. In this paper, we describe a data collection and distribution architecture that enables gathering physical parameters of a large data center at a very high temporal and spatial resolution of the sensor measurements. We think this is an important characteristic to enable more accurate heat-flow models of the data center and with them, find opportunities to optimize energy consumption. Having a high resolution picture of the data center conditions, also enables minimizing local hotspots, perform more accurate predictive maintenance (pending failures in cooling and other infrastructure equipment can be more promptly detected) and more accurate billing. We detail this architecture and define the structure of the underlying messaging system that is used to collect and distribute the data. Finally, we show the results of a preliminary study of a typical data center radio environment.