Stream-based data management enables the efficient analysis and processing of large volumes of data in distributed environments. This book presents network-aware optimization techniques which allow an effective resource usage considering computational load and network bandwidth in a distributed data stream management system. The data stream sharing approach is thereby based on distributing query processing in the network and on sharing preprocessed data streams for satisfying multiple similar queries. To increase the possibilities for sharing, the extended approach of data stream widening is able to alter existing streams to additionally contain all the necessary data for a new query. Since data stream widening requires the treatment of disjunctive predicates, this book further describes methods for matching and evaluating such predicates. The book is thus a suitable source of information for computer scientists and engineers interested in the optimized processing, evaluation, and management of distributed data streams.