## 1 Introduction  
In recent years multimedia content provisioning via the Internet has been dramatically increasing. The resulting multimedia systems typically store media content on a dedicated server. Popular systems, especially in the entertainment area, occurred with the classic video-on-demand (VoD) systems. These static and centralized systems have a low protocol overhead and can, therefore, efficiently broadcast their video content to many different client devices. However, the content is only available in certain data formats and encodings. Over the years the variety of different client devices has been steadily increasing. Thus, the content has to be adapted to the special needs of each individual user, respectively his/her technical device. To allow for such an adaptation, user preferences and terminal capabilities as offered by MPEG-21 DIA (Digital Item Adaptation) are used [1]. A lot of work has already been done in the area of so-called knowledge-based multimedia adaptation systems. These systems use terminal capabilities and content descriptions to dynamically adapt the desired multimedia content. All adaptation processes take place on one single dedicated server. Nevertheless, they also offer individual workflows that are created during a planning phase [2]. To handle the multimedia transformation problem, most approaches use classical'state space planning problem' and typical AI-based planning algorithms. Nowadays, there are already efforts to decompose monolithic multimedia systems. The most prominent example is the area of simple media streaming, e.g., for Internet Protocol Television (IPTV). Here, the current trend is to use flexible peer-to-peer (P2P) architectures. There are already several implementations available using different overlay topologies. The most popular system is currently PPLive [3] with more than 50 million registered users. Also the European IPTV market is growing fast, for instance Zattoo [4] gained one million users within the last two years. However, all these applications rely on a simple data streaming scenario. When it comes to more complex tasks, like media adaptation, P2P systems are not used. This is because complex scenarios make great demands on the system components regarding processing power and reliability. In P2P systems these basic conditions cannot be achieved out of the box; P2P systems are unreliable and not every peer is able to fulfill cost expensive media adaptation tasks, e.g., transcoding or scaling, which means that the content is rather static. Our primary goal is to combine the best of both worlds: the individual adaptation of multimedia content as it is done in knowledge-based adaptation systems, and the flexible, distributed architecture of P2P systems. The idea of service-oriented DIA has already been discussed in developing knowledge-based multimedia adaptation systems, but has largely been rejected for efficiency reasons (see e.g., [5]). In contrast, we will show, in the course of this paper, that it is indeed possible to dynamically adapt multimedia content to the special needs of each individual user in real-time on its way through the network using a service-oriented architecture. Please note, due to the high demands of multimedia streaming, we decided to evaluate our system considering soft real-time constraints. Figure 1 shows a classification of the different technologies. The shaded areas visualize the efficiency of the systems. Classic VoD systems show a very high efficiency due to their low protocol overhead. With the increase of the protocol overhead due to distribution and dynamics the efficiency decreases. We already argued that it is difficult to use P2P technology as bases for adaptation workflows due to the limited devices capabilities. Therefore, we focus on distributing workflow components used in knowledge-based adaptation systems. In the Web community, the decomposition of complex workflows into smaller independent entities is already a common task for business applications.