The recent advance in wireless network technologies has enabled the streaming media service on the mobile devices such as PDAs and cellular phones. Since the wireless network has low bandwidth channels and mobile devices are actually composed of limited hardware specifications, the transcoding technology is needed to adapt streaming media to the given mobile devices. When large scale mobile clients demand the streaming service, load distribution Methods among transcoding servers highly impact on the total number of QoS streams. In this paper, the resource weighted load distribution Method is proposed for the fair load distribution and the more scalable performance in distributed transcoding servers. Our proposed Method is based on the weight of resources consumed for transcoding to classified client grades and the maximum number of QoS streams actually measured in transcoding servers. The proposed policy is implemented on distributed transcoding system. In experiments, we evaluate its fair load distribution and scalable performance according to the increase of transcoding servers.

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In the ubiquitous computing environment a user may interact with a large number of devices. The publish/subscribe paradigm is suitable for the various applications by allowing the subscribers to declare their interests and receive only the notifications of interest. This paper propose a novel event filtering approach preventing waste in the space of the event queue of the event channel due to unwanted events and reducing the network load. Performance evaluation reveals that the proposed scheme displays significant improvement over the existing event service, Java messaging service (JMS) and Omnievent service in terms of event delivery time for various numbers of servers and data sizes.