## 2 Related Work  
In the multimedia community a lot of work has been invested in the area of multimedia adaptation systems. In [5] a knowledge-based adaptation framework is presented that supports dynamic composition and execution of multimedia transformations using existing software libraries. A knowledge-based planner computes a sequence of required adaptation steps based on the available libraries and the user requirements. All transformation steps are fulfilled on one single server. The concept was validated using standard multimedia adaptation libraries and a state-space planning engine. A further development of this work is described in [2]; here the focus lies on automatic generation of proper adaptation workflows. Moreover, the authors enhanced their framework by integrating semantic languages (like OWL-S) to ease the planning process. A very similar approach, called CAIN, is presented in [12]. Here, also workflows are built from a series of basic content adaptation tools, but instead of only considering technical capabilities of the client device and resource limitations, user preferences are used in addition to retrieve suitable workflows. The introduced adaptation decision taking algorithm relies on a constraint matching problem: resource limitations _versus_ terminal capabilities. If multiple adaptation strategies are found to match these constraints: the one which matches the most constraints of the user preferences is chosen. In summary, all common systems in the multimedia community are focused on adaptation processes that run on a dedicated server, whereas our idea is to distribute different adaptation steps to different service providers. Also in the P2P community media streaming has recently received attention. In [13] the authors present DONet, a Data-driven Overlay Network for live media streaming. A smart partner selection algorithm and a low-overhead scheduling algorithm to pull data from multiple partners are presented. Moreover, the key issues of an Internet-based implementation are discussed, called CoolStreaming: the pioneer in the field of IPTV (Internet Protocol Television). Nowadays, IPTV applications have seen a dramatic rise in popularity and, furthermore, have received significant attention from industry and academia, e.g., PPLive or Sopcast. Currently, PPLive is the most popular instance of an IPTV application with more than 50 million subscribers. Due to its popularity, many measurement studies for the PPLive system have been performed. The results in [14] show significant playback time lags between different peers and long startup delays. The startup delay is the time interval from when one channel is selected until actual playback starts on the screen. It depends on the popularity of the chosen channel and takes for less popular channels up to two minutes. Since a large percentage of participate nodes are behind network address translation (NAT) boxes or firewalls the lengthy startup times and high failure rates are inherent problems in P2P streaming systems (see [15]). The experiments in [16] show that the characteristics of P2P file-sharing overlays depend on the application atop the P2P overlay. In typical P2P file sharing systems content is downloaded in the background before consumption by the user, therefore session lengths will be quite long. In contrast, in IPTV systems users are actively present and want to start consuming content right away. Therefore, session lengths are shorter and client nodes are impatient, _i.e._, the media playback has to start in a timely manner. Moreover, all P2P applications rely on a simple data streaming scenario without any personalization or adaptation of media content. For such complex tasks P2P systems are unsuitable. In a media adaptation scenario great demands are made on the system regarding processing power and reliability. But not every peer in a P2P environment is able to fulfill cost expensive media adaptation tasks, e.g., transcoding or scaling.