The high bandwidth and low latency of the modern internet has made possible the deployment of distributed computing platforms. The XenoServer platform provides a distributed computing platform open to all and presents three major new challenges for resource discovery: Firstly, network location is key for effectively provisioning services, to mitigate against high-latency, high-load or component failure. Secondly, many services require a presence on several servers, with inter-related requirements. Finally, as the platform is open with respect to users and servers, large numbers of queries and updates are expected. To address these requirements we introduce and evaluate Xeno-Search, a new distributed service for selecting the machines to host components of multi-node distributed systems and which is uniquely able to express and efficiently answer complex queries with inter-related location constraints. We demonstrate that Xeno-Search represents a trade-off between accuracy and query time which avoids exhaustive search and supports multiple resources. In addition the performance of the algorithm and the quality of its server selections is investigated and the performance of the distributed service shown to be invariant as the number of nodes or items indexed increases.

A new method for content-based image retrieval is being presented. This method uses a vector-space model to represent images in a multidimensional space. This model allows the use of multiple attributes in the retrieval process and also identifies the most selective values for each attribute. Therefore by ignoring the less significant values the user can reduce the dimensionality of the feature set and simplify the vector model. It also allows the user to choose any similarity measure depending on the application. The user can also assign weights to the different attributes depending on the retrieval mechanism intended. These characteristics of the retrieval method increase the retrieval efficiency and makes the model very flexible as it can be used universally for retrieving images from different domains. Keywords: Content-Based Image Retrieval, Multimedia Information Database Systems 1 Introduction The digital revolution has resulted in an increase in the number and siz...