In this paper, we propose a service differentiation incentive for P2P streaming system, according to peers' instant contributions. Also, a repeated game model is designed to analyze how much the peers should contribute in each round under this incentive. Simulations show that satisfying streaming quality is achieved in the Nash Equilibrium state.

In the large scale multimedia interactive applications over the Internet, data can be categorized into the streaming data (e.g. the audio and the video streaming) and the sporadic data (e.g. the annotation in a whiteboard). The mesh-pull overlay fits for the streaming data, for it is resilient in heterogeneous network, while the tree-push overlay is more suitable for the sporadic data, for its easy-to-manage structure can solve the problem of packet loss and disorder. To address the transmission of both types of data, a Hybrid Mesh/Tree Overlay (HyMTO) is proposed in this paper, where the sporadic data and the streaming data are transmitted through different overlays with a novel synchronous scheme. HyMTO can provide the resilient, reliable and ordered transmission for both types of data respectively. Simulations are presented to evaluate the effectiveness and efficiency of HyMTO and a practical e-conference system based on HyMTO is implemented and deployed to demonstrate its practicability and reasonability.

Service composition allows distributed application, such as multimedia application, to be composed from atomic service units and to adapt dynamically to users' requirements and environment conditions in pervasive computing system. It augments the adaptation action space for the application of pervasive computing. According to the multidimensional QoS (Quality of Service) requirement of pervasive computing system, we proposed a comprehensive service composition method to enhance the capability of application adaptation. First, according to a hierarchy policy model and a policy specification language, strengthened by event calculus, service discovery policy action integrating the situation of user, application, environment and resource can be triggered. Secondly, the proposed physical space model can support the location-aware service discovery and explicit range query to improve the efficiency of the query. To the end, an adaptation policy evaluation model is utilized to maximize an evaluation criterion–quality of satisfaction of users and environment by optimizing the optional service selection and the composition path. Through experiment and discussion of the algorithm, the paper further illustrates the great potential advantage of the solution to service composition.

Layered streaming in P2P networks has become a hot topic recently. However, the "layered" feature makes the data scheduling quite different from that for nonlayered streaming, and it hasn't been systematically studied yet. In this paper, first, according to the unique characteristics caused by layered coding, we present four objectives that should be addressed by scheduling: throughput, layer delivery ratio, useless packets ratio, and subscription jitter prevention; then a three-stage scheduling approach LayerP2P is designed to request data, where the min-cost flow model, probability decision mechanism, and multiwindow remedy mechanism are used in Free Stage, Decision Stage, and Remedy Stage, respectively, to collaboratively achieve the above objectives. With the basic version of LayerP2P and corresponding experiment results achieved in our previous work, in this paper, more efforts are put on its mechanism details and analysis to its unique features; besides, to further guarantee the performance under sharp bandwidth variation, we propose the enhanced approach by improving the Decision Stage strategy. Extensive experiments by simulation and real network implementation indicate that it outperforms other schemes. LayerP2P has also been deployed in PDEPS Project in China, which is expected to be the first practical layered streaming system for education in P2P networks.

Although layered streaming in heterogeneous peer-to-peer networks has drawn great interest in recent years, there's still a lack of systematical studies on its data scheduling issue. In this paper, we propose a new scheduling approach for layered video streaming, called LayerP2P. The key idea and main contributions of LayerP2P come in two-fold: 1) According to the characteristics caused by layered coding, we propose four objectives that should be achieved by data scheduling: high throughput, high layer delivery ratio, low useless packets ratio, and low subscription jitter; 2) We design a 3-stage scheduling mechanism to request absent blocks, where the min-cost flow model, probability decision mechanism and multi-window remedy mechanism are employed in Free Stage, Decision Stage and Remedy Stage, respectively. Each stage has different scheduling objective while collaborates with each other, to achieve the above four objectives. Experimental results indicate that our approach outperforms other schemes in simulation environment. Besides, LayerP2P is implemented in the PDEPS Project in China, which is expected to be the first practical layered streaming system for education in peer-to-peer networks.

Layered streaming in overlay networks has drawn great interests since not only can it accomodate large scales of clients but also it handles client heterogeneities. However, to our knowledge, there's still a lack of overlay construction (i.e. neighbor selection) approach suited for layered streaming, because i) In existing works neighbors are selected only based on their network conditions. However, a neighbor with good network condition may not be able to provide sufficient layers (e.g. a neighbor in the same LAN), ii) Previous works usually select "good" neighbors for the new node, ignoring that the joining of the new node could also be utilized to improve the performance of existing nodes. In this paper, OCals - a two-stage QoS aware overlay construction approach for layered streaming is proposed. The main contribution of OCals is that i) when selecting neighbor, it considers existing nodes' network conditions and their providing layers as a whole; ii) it guarantees the QoS for the new node as well as improves the QoS for existing nodes so that with the joining of new nodes, the performance of the overlay could be consecutively improved; iii) it's easy to implement and low time cost. Experiments demonstrate that compared with two other approaches: SCAMP (a pure random neighbor selection method) and Narada (a QoS aware method), the throughput and average packet delay of the layered streaming on top of the overlay constructed by OCals can be remarkably improved. Besides, the time spent on joining and recovery is very short.

Layered video streaming in peer-to-peer networks has drawn great interests since not only it can accommodate a large number of users but also it handles heterogeneities of client networks. However, to our knowledge, there's still a lack of systematical study on the data scheduling (i.e. requesting and relaying data) for layered streaming, and previous works in this area just focus on maximizing the throughput and/or minimizing the packet delay. In this paper, firstly, according to the characteristics caused by layered coding, we propose the four objectives that should be achieved by data scheduling for layered streaming: high throughput, high layer delivery ratio, low useless packets ratio and low subscription jitter; then, we use a 3-stage scheduling approach to request missed blocks, where each stage has different scheduling objective but collaborate with each other. The min-cost network flow model, probability decision mechanism and multi-window remedy mechanism are employed in Free Stage, Decision Stage and Remedy Stage, respectively, to achieve the above four goals. Extensive experimental results indicate that our approach outperforms other schemes in both throughput and layer delivery ratio. Besides, the useless packets number and subscription jitters are kept low.

The push method for data transmission in peer-to-peer system has drawn great interest, since it can efficiently reduce the accumulated latency observed at user nodes. However, it can cause redundant packets more easily than the pull method, because the nodes using pull method can completely control the data request process while it's not the case for push method. In this paper, we systematically study the distribution of the received redundant packets in push mode, and model it as a heterogeneous Poisson arrival. Both the theoretical analysis and the simulation show that the redundant packets caused by push method can be remarkable if the end-to-end delays among peers are not small enough. Furthermore, a redundant packets preventing strategy is proposed, and the experiment on PlanetLab demonstrates that it can effectively reduce the amount of received redundant packets.

With the aid of mobile technology, it's possible to carry out collaborative learning (CL) in any places at any time. And the most essential and effective way to achieve this goal is through real-time multimedia discussion. In this paper, a multi-agent system, ErmdClime, is designed and implemented to enable real-time multimedia discussion for collaborative learning in mobile environment. The realtime bi-directional audio/video interaction and shared white board are integrated seamlessly into the system for learners with mobile devices. Besides, this system enables both local and remote learners to control the play of PowerPoint slides by voice command when discussing and annotate on the shared white board. Context-aware technology is used to switch real video and white board display on mobile devices. User study demonstrates that learners feel quite natural and highly efficient when they are engaged in the CL with mobile devices in our system