Current interactive tele-presence systems are designed and optimized for one particular type of cyber-physical activity such as conversation, video chat, or gaming. However, with the emerging new 3D tele-immersive (TI) systems, such as our own TI system, called TEEVE (TEle-immersion for EVErybody), we observe that the same TI system platform is being used for very different activities. In this paper, we classify the TI activities with respect to their physical characteristics, qualitatively analyze the cyber side of TI activities, and argue that one needs to consider very different performance profiles of the same TI system platform in order to achieve high quality of experience (QoE) for different cyber-physical TI activities.

Internet service providers (ISP) apply traffic engineering (TE) in the underlay network to avoid congestion. On the other hand, content providers (CP) use different server selection (SS) strategies in the overlay network to reduce delay. It has been shown that a joint optimization of TE and SS is beneficial to the performance from both ISP's and CP's perspectives.One challenging issue in such a network is to design a distributed protocol which achieves optimality while revealing as little information as possible between ISP and CP. To address this problem, we propose a distributed protocol termed PETS, in which each router of ISP makes independent traffic engineering decision and each server of CP makes independent server selection decision. We prove that PETS can achieve optimality for the joint optimization of TE and SS. We also show that PETS can significantly reduce message passing and enables ISP to hide important underlay network information (e.g., topology) from CP. Furthermore, PETS can be easily extended to handle the case of multiple CPs in the network.

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.

Abstract-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 crosstraffic), 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.