Video surveillance systems are playing an important role to protect lives and assets of individuals, enterprises and governments. Due to the prevalence of wired and wireless access to Internet, it would be a trend to integrate present isolated video surveillance systems by applying distributed computing environment and to further gestate diversified multimedia intelligent surveillance (MIS) applications in ubiquity. In this paper, we propose a distributed and secure architecture for ubiquitous video surveillance (UVS) services over Internet and error-prone wireless networks with scalability, ubiquity and privacy. As cloud computing, users consume UVS related resources as a service and do not need to own the physical infrastructure, platform, or software. To protect the service privacy, preserve the service scalability and provide reliable UVS video streaming for end users, we apply the AES security mechanism, multicast overlay network and forward error correction (FEC), respectively. Different value-added services can be created and added to this architecture without introducing much traffic load and degrading service quality. Besides, we construct an experimental test-bed for UVS system with three kinds of services to detect fire and fallincident features and record the captured video at the same time. Experimental results showed that the proposed distributed service architecture is effective and numbers of services on different multicast islands were successfully connected without influencing the playback quality. The average sending rate and the receiving rates of these services are quite similar, and the surveillance video is smoothly played.

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To roam between homogeneous or heterogeneous wireless networks, such as prevalent WiFi and 3.5G or emerging WiMAX, a mobility management plays an important role to provide users ubiquitous Internet access and seamless connections. Most of techniques in mobility management focus on shortening the delay of roaming from one wireless domain to another. Pre-registration is one of cross-layer methods to trigger layer-3 handotT before layer-2 handotT to further decrease handoff delay. Pre-registration applies prediction method to forecast next network destination of MN. However, prediction failure will bring a lengthy handoff delay and burst packets loss because MN will perform original hand off scheme in Mobile IP when entering an unexpected network. In this paper, a new mobility management protocol named predictive multiple pre-registration (PMP)" is proposed to increase the success rate of handotT prediction by pre-registering multiple target networks which MN may associate with. Then, the QoS of mobile multimedia streaming can be also improved by PMP due to the reduced packet loss and reduced handoff latency. The performance results from experiments on typical multimedia applications of VoD and VoIP demonstrate that the proposed PMP further improve the QoS of mobile multimedia streaming by the perceptual quality indices of PSNR and MOS values of VoD and VoIP applications respectively.

In large vehicles such as a train, passengers can access Internet through an in-vehicle mobile router to effectively reduce the cost and overhead of roaming to a new network. While we apply the idea of mobile network into large vehicles, the critical issue is how to build up seamless Internet access services between vehicle's mobile network and fixed networks along the moving path or stations. Mobile router is constructed by the technologies of Mobile IP and double IP tunneling. Through the mobile router, the mobile network in large vehicles can provide passengers a seamless Internet access with the access points outside. However, mobile router inherits the QoS issues in Mobile IP. In this paper, we apply the idea that large vehicles usually have a fixed or predictive moving path to propose a PPT (Predictive Packet Transmission) scheme to improve the quality of Internet access service in mobile network. Through theoretical analysis and preliminary experiment, we demonstrate that the proposed PPT scheme can reduce not only the network handoff time but also the packet loss.