vSkyConf: Cloud-assisted Multi-party Mobile Video Conferencing

As an important application in the busy world today, mobile video conferencing facilitates virtual face-to-face communication with friends, families and colleagues, via their mobile devices on the move. However, how to provision high-quality, multi-party video conferencing experiences over mobile devices is still an open challenge. The fundamental reason behind is the lack of computation and communication capacities on the mobile devices, to scale to large conferencing sessions. In this paper, we present vSkyConf, a cloud-assisted mobile video conferencing system to fundamentally improve the quality and scale of multi-party mobile video conferencing. By novelly employing a surrogate virtual machine in the cloud for each mobile user, we allow fully scalable communication among the conference participants via their surrogates, rather than directly. The surrogates exchange conferencing streams among each other, transcode the streams to the most appropriate bit rates, and buffer the streams for the most efficient delivery to the mobile recipients. A fully decentralized, optimal algorithm is designed to decide the best paths of streams and the most suitable surrogates for video transcoding along the paths, such that the limited bandwidth is fully utilized to deliver streams of the highest possible quality to the mobile recipients. We also carefully tailor a buffering mechanism on each surrogate to cooperate with optimal stream distribution. We have implemented vSkyConf based on Amazon EC2 and verified the excellent performance of our design, as compared to the widely adopted unicast solutions.Comment: 10 page

Development of Campus Video-Conference System Based on Peer-To-Peer Architecture

Peer to Peer (P2P) systems inherently have high scalability, robustness and fault tolerance because there is no centralized server and the network self-organizes itself. This is achieved at the cost of higher latency for locating the resources of interest in the P2P overlay network. This paper describes the design and implementation of campus video conference system based on P2P architecture that was tested within premises of Ladoke Akintola University of Technology, Ogbomoso, Nigeria. The proposed Campus video conference system is made up of five modules which are the media stream engine, the conferencing control protocol, transmission module, TCP/UDP module and the user interface module. The media stream engine is responsible for audio/video capture and playback, the conferencing control protocol defines a set of conventions governing the structure and behavior of communication messages, the transmission module consists of a peer and a distribution network constituting of the peers also the delivery and exchange of streaming data while the audio manager and video manager use TCP/UDP to broadcast to other peer. The proposed system will offer smooth video conferencing with low delay and seldom and short freezes. It is believed that this videoconference system will bring video telephony to a new level of quality and will lead to a new trend in everyday communications in the university community

Cost-effective low-delay cloud video conferencing

The cloud computing paradigm has been advocated in recent video conferencing system design, which exploits the rich on-demand resources spanning multiple geographic regions of a distributed cloud, for better conferencing experience. A typical architectural design in cloud environment is to create video conferencing agents, i.e., virtual machines, in each cloud site, assign users to the agents, and enable inter-user communication through the agents. Given the diversity of devices and network connectivities of the users, the agents may also transcode the conferencing streams to the best formats and bitrates. In this architecture, two key issues exist on how to effectively assign users to agents and how to identify the best agent to perform a transcoding task, which are nontrivial due to the following: (1) the existing proximity-based assignment may not be optimal in terms of inter-user delay, which fails to consider the whereabouts of the other users in a conferencing session; (2) the agents may have heterogeneous bandwidth and processing availability, such that the best transcoding agents should be carefully identified, for cost minimization while best serving all the users requiring the transcoded streams. To address these challenges, we formulate the user-to-agent assignment and transcoding-agent selection problems, which targets at minimizing the operational cost of the conferencing provider while keeping the conferencing delay low. The optimization problem is combinatorial in nature and difficult to solve. Using Markov approximation framework, we design a decentralized algorithm that provably converges to a bounded neighborhood of the optimal solution. An agent ranking scheme is also proposed to properly initialize our algorithm so as to improve its convergence. The results from a prototype system implementation show that our design in a set of Internet-scale scenarios reduces the operational cost by 77% as compared to a commonly-adopted alternative, while simultaneously yielding lower conferencing delays.published_or_final_versio

Distributed Rate Allocation in Switch-Based Multiparty Videoconferencing System

Multiparty videoconferences, or more generally multiparty video calls, are gaining a lot of popularity as they offer a rich communication experience. These applications have, however, large requirements in terms of both network and computational resources and have to deal with sets of heterogenous clients. The multiparty videoconferencing systems are usually either based on expensive central nodes, called Multipoint Control Units (MCU), with transcoding capabilities, or on a peer-to-peer architecture where users cooperate to distribute more efficiently the different video streams. Whereas the first class of systems requires an expensive central hardware, the second one depends completely on the redistribution capacity of the users, which sometimes might neither provide sufficient bandwidth nor be reliable enough. In this work we propose an alternative solution where we use a central node to distribute the video streams, but at the same time we maintain the hardware complexity and the computational requirements of this node as low as possible, e.g. it has no video decoding capabilities. We formulate the rate allocation problem as an optimization problem that aims at maximizing the Quality of Service (QoS) of the videoconference. We propose two different distributed algorithms for solving the optimization problem: the first algorithm is able to find an approximate solution of the problem in a one-shot execution, whereas the second algorithm, based on Lagrangian relaxation, performs iterative updates of the optimization variables in order to gradually increase the value of the objective function. The two algorithms, though being disjointed, nicely complement each other. If executed in sequence, they allow to achieve both, a quick approximate rate reallocation in case of a sudden change of the system conditions, and a precise refinement of the variables which avoids problems caused by possible faulty approximate solutions. We have further implemented our solution in a network simulator where we show that our rate allocation algorithm is able to properly optimize users' QoS. We also illustrate the benefits of our solution in terms of network usage and overall utility when compared to a baseline heuristic method operating on the same system architecture

Cooperative video streaming on smartphones

Video streaming is one of the increasingly popular, as well as de-manding, applications on smartphones today. In this paper, we con-sider a group of smartphone users, within proximity of each other, who are interested in watching the same video from the Internet at the same time. The common practice today is that each user down-loads the video independently using her own cellular connection, which often leads to poor quality. We design, implement, and evaluate a novel system, MicroCast, that uses the resources on all smartphones of the group in a co-operative way so as to improve the streaming experience. Each phone uses simultaneously two network interfaces: the cellular to connect to the video server and the WiFi to connect to the rest of the group. Key ingredients of our design include the follow-ing. First, we propose a scheduling algorithm, MicroDownload, that decides which parts of the video each phone should download from the server, based on the phones ’ download rate. Second, we propose a novel all-to-all local dissemination scheme, MicroNC-P2, for sharing content among group members, which outperforms state-of-the-art peer-to-peer schemes in our setting. MicroNC-P2 is designed to exploit WiFi overhearing and network coding, based on a local packet broadcast framework, MicroBroadcast, which we developed specifically for Android phones. We evaluate MicroCast on a testbed consisting of seven Android phones, and we show that it brings significant performance benefits without battery penalty