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Workspace awareness is one of the key issues in real-time collaborative editing system (CES). It is knowledge about the state of a particular environment, thus needs frequent exchange of information about other collaborators and the whole group. Bitmap-based collaborative graphics editing systems are a special class of CESs. Because of the intrinsic characteristics of bitmap, the data-streams need to be exchanged in the network will increase dramatically. On the other hand, different collaborators in one collaborative group may have different collaborative requirement and different network environment. So it is not wise to deliver the same large data-stream to distinct receivers. Instead, we propose a multi-level coding method, which encodes each bitmap operation into several different granularities. As a result, different collaborators receive different data-stream in different granularity according to their current requirement and network condition. In addition, we also propose a self-adaptive awareness model by combining the awareness model with network QoS. It adjusts the awareness strategy and awareness coefficient intelligently to make the awareness model adaptive to the network condition. It also reallocates the network resources among the whole collaborative group, thus optimizes the collaborative effect.