No abstract

We present a dynamic semantic data replication scheme called DSDR for classic k-random search in unstructured peer-to-peer (P2P) networks. During its k-random search each peer periodically updates its local view on the semantic overlay of the network based on observed queries (demand) and received information about provided items (supply), in particular their semantics. Peers dynamically form potentially overlapping groups for semantically equivalent or similar items they are actually demanding. Besides, each peer predicts the number of needed item replicas in the future based on its local observations in the past. The decision of which item to best replicate to which member is made within each demander group based on the maximal expected utility, traffic costs, and plausibility of such replication. Our experimental evaluation evidences that k-random search with DSDR-based replication can significantly outperform its combination with a nearoptimal but non-semantic replication strategy, as well as a peer expertise-based semantic P2P search without replication.

The convergence of information technologies (IT) has enabled the Digital Enterprise in which engineering, production planning, manufacturing and sales processes are supported by IT-based collaboration, simulation and enactment. As a result, borders between reality and its virtual representations become increasingly blurred. Advanced tools need to support flexibility, specialization and collaborative evolution of the design where the exchange of knowledge between domain experts helps to improve informed decision making. In this paper, we present a collaborative, web-based framework to create 3D scenarios for product design, simulation and training assisted by animated avatars.

In this paper, we present iRep3D 2.0, a semanticbased repository for efficient deep search of 3D scenes in X3D, XML3D and COLLADA. It supports real time hybrid semantic retrieval of 3D scenes in terms of their syntactic, conceptual, functional and geometric features. This is enabled via off-line indexing over annotated 3D (sub-) scenes with respect to different aspects of semantics and parallel sub-query processing. In addition, an efficient incremental (re-)indexing strategy is derived for iRep3D 2.0, which offers the quick adaption of system to the updates of 3D scene annotations. Further, iRep3D 2.0 in particular scales to advanced semantic deep search and reuse of relevant sub-scenes down to the individual object level of a scene. For this, sub-scene extraction method for XML-based 3D scenes is performed in case that a new scene is being indexed. Finally, the repository comes with a web-based graphic user interface together with a 3D scene annotation toolkit for both non-experts and expert users.

Mobile peer-to-peer (P2P) computing with applications such as for video on demand, file sharing, and video conferencing is gaining momentum based on new standards and technologies such as IETF PPSP, WiFi-Direct and BitTorrent live streaming. In this paper, we describe the mobile system MyMedia, that allows users to search, share and experience videos and live recordings using P2P and at the best quality possible with respect to available network capacity. In particular, the MyMedia system features a high-precision semantic P2P search and dynamic network-adaptive P2P live streaming of MPEG videos over HTTP based on the ISO/IEC standard MPEG-DASH from mobile to mobile devices in unstructured wireless P2P networks. Experimental evaluation of these features in terms of performance and energy consumption, and a first, limited evaluation of user acceptance at a film festival showed that the MyMedia system is suitable for its purpose. The MyMedia system is available as open-source software for the Android operating system.