3D Tele-Immersion (3DTI) system brings 3D data of people from geographically distributed locations into the same virtual space to enable interaction in 3D space. One main obstacle of designing 3DTI system is to overcome its high bandwidth requirement when disseminating the 3D data over the network. Bandwidth adaptation framework is needed to handle the heterogeneity of the available network throughput. In this work, we propose an object-level bandwidth adaptation framework for 3DTI system (OBA3D). Unlike existing adaptation frameworks which work at the frame level or Group-of-picture (GOP) level, OBA3D takes advantage of the 3D semantics contained in the 3D frame. It conducts bandwidth adaptation at the object-level and achieves more fine-grained control over 3D video quality. We evaluate the performance of OBA3D on a real 3DTI testbed. OBA3D is shown to achieve good quality-of-experience when the network throughput is substantially lower than the required bandwidth for data transmission.

In view of the different demands on quality of service of different user activities in the 3D Tele-immersive (3DTI) environment, we combine activity recognition and real-time morphing-based compression and present the Activity-Aware Adaptive Compression. We implement this scheme on our 3DTI platform: the TEEVE Endpoint, which is a runtime engine to handle the creation, transmission and rendering of 3DTI data. User study as well as objective evaluation of the scheme show that it can achieve 25% more bandwidth saving compared to conventional 3D data compression as zlib without perceptible degradation in the user experience.

We present TEEVE Endpoint, which is a runtime engine to handle the creation, transmission and rendering of 3D Tele-immersive (3DTI) data and provides application programming interfaces (APIs) to developers to easily create 3DTI applications.

We study providing large-scale video-on-demand (VoD) service to distributed users. In order to achieve scalability in user capacity and reduce the load of the core network, local servers with heterogeneous storage are deployed. Each server replicates the movie segments depending on their access probabilities. Considering the realistic scenario that underlay delay is a function of the total traffic in the link (including cross-traffic), we address two important problems to achieve low user interactive delay: 1) Which segments should each server replicate under the constraints of their capacities to achieve network-wide good locality effect? This is the so-called content replication (CR) problem; and 2) Given a number of remote servers with the requested segment, which one should serve the user? This is the so-called server selection (SS) problem. CR and SS problems couple with each other. In this paper, we propose a simple and distributed algorithm which seeks to jointly optimize CR and SS. The algorithm, termed CR-SS, achieves good caching locality by adaptively replacing segments and selecting servers with a simple lookup. Simulation results on Internet-like topologies show that CR-SS outperforms existing and state-of-the-art approaches by a wide margin, achieving substantially lower user delay.

Wireless mesh networks (WMNs) have been increasingly used to carry multimedia traffic with flow requirements. The performance of multi-radio multi-channel (MRMC) WMNs largely depends on the routing and channel assignment. Because routing and channel decisions are coupled, they need to be jointly optimized to achieve the best performance. This is the so-called routing and channel assignment (RCA) problem, which is known to be NP-hard. There has not been sufficient consideration on joint RCA optimization which takes into account multimedia traffic demands in the network. In this paper, we propose and study CRAFT (Channel and Routing Assignment with Flow Traffic) for MRMC WMNs. CRAFT is distributed, cooperative, computationally efficient and simple to implement. It jointly optimizes routing and channel assignment by using a properly designed objective function to meet the flow demands of the mesh nodes. Simulation results based on NS3 show that CRAFT performs much better than other state-of-the-art schemes in terms of convergence, delay, loss rate and throughput.

3D Tele-immersion (3DTI) system enables geographically distributed users to interact with each other in the virtual 3D space. Many 3DTI applications require users to have frequent physical movement in the application (e.g, 3D interactive exergaming, remote therapy). However, traditional user interaction (UI) solution (which includes large display, mouse/keyboard) for 3DTI system does not give users much freedom to move during the interaction and thus has difficulties to meet this requirement. In this work, we design and implement a novel UI solution TEEVE-Remote which utilizes state-of-the-art camera, mobile phone and display technologies to overcome the difficulties and therefore significantly improve the user experience of 3DTI system.

In video streaming over multicast network, user bandwidth requirement is often heterogeneous possibly with orders of magnitude difference (say, from hundreds of kb/s for mobile devices to tens of Mb/s for high-definition TV). Multiple description coding (MDC) can be used to address this bandwidth heterogeneity issue. In MDC, the video source is encoded into multiple independent descriptions. A receiver, depending on its available bandwidth, joins different descriptions to meet their bandwidth requirements. An important but challenging problem for MDC video multicast is how to assign bandwidth to each description in order to maximize overall user satisfaction. In this paper, we investigate this issue by formulating it as an optimization problem, with the objective to maximize user bandwidth experience by taking into account the encoding inefficiency due to MDC. We prove that the optimization problem is NP-hard. However, if the description number is larger than or equal to a certain threshold (e.g., if the minimum and maximum bandwidth requirements are 100 kb/s and 10 Mb/s, respectively, such threshold is seven descriptions), there is an exact and simple solution to achieve maximum user satisfaction, i.e., meeting all the bandwidth requirements. For the case when the description number is smaller, we present an efficient heuristic called simulated annealing for MDC bandwidth assignment (SAMBA) to assign bandwidth to each description given the distribution of user bandwidth requirement. We evaluate our algorithm using simulations. SAMBA achieves virtually the same optimal performance based on exhaustive search. By comparing with other assignment algorithms, SAMBA significantly improves user satisfaction. We also show that, if the coding efficiency decreases with the number of descriptions, there is an optimal description number to achieve maximal user satisfaction.

Multiple description coding (MDC) has been widely used in media streaming to address the bandwidth heterogeneity issue. That is, the video source encodes data into multiple descriptions. At the receiver end, the streaming quality is proportional to the number of descriptions received. In this paper, we investigate how to assign bandwidth for descriptions in order to make full use of available network bandwidth. We formulate the problem as an optimization problem. We then decompose the problem and address it by an iterative algorithm. We evaluate the algorithm through simulations. Our results show that arbitrary description rates may severely degrade system performance and an optimal solution can make efficient use of network bandwidth.