In this paper, we describe several enhancement techniques to improve the state-of-the-art stream prefetcher. First, the enhanced stream prefetcher takes streams with long stride into consideration to avoid wasteful prefetches. Second, accessing a node in a tree or graph structure may have a different direction than the traversal direction through the structure. The enhanced stream prefetcher el...

We study various operations for partitioning, projecting and merging streams of data. These operations are motivated by their use in dataflow programming and the stream processing languages. We use the framework of stream calculus and stream circuits for defining and proving properties of such operations using behavioural differential equations and coinduction proof principles. We study the inv...

The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in data stream mining, dating back to the 1980s. Many applications rely directly or indirectly on finding the frequent items, and implementations are in use in large scale industrial systems. However, there has not been mu...

Emerging large-scale monitoring applications rely on continuous tracking of complex data-analysis queries over collections of massive, physically-distributed data streams. Thus, in addition to the spaceand time-efficiency requirements of conventional stream processing (at each remote monitor site), effective solutions also need to guarantee communication efficiency (over the underlying communic...

Real-time event stream processing (RT-ESP) applications must synchronize continuous data streams despite fluctuations in resource availability. Satisfying these needs of RT-ESP applications requires predictable QoS from the underlying publish/subscribe (pub/sub) middleware. If a transport protocol is not capable of meeting the QoS requirements within a dynamic environment, the middleware must b...

Emerging large-scale monitoring applications rely on continuous tracking of complex data-analysis queries over collections of massive, physically-distributed data streams. Thus, in addition to the spaceand time-efficiency requirements of conventional stream processing (at each remote monitor site), effective solutions also need to guarantee communication efficiency (over the underlying communic...

The recent rise of smart applications has drawn interest to logical reasoning over data streams. Different query languages and stream processing/reasoning engines were proposed. However, due to a lack of theoretical foundations, the expressivity and semantics of these diverse approaches were only informally discussed. Towards clear specifications and means for analytic study, a formal framework...

In many applications such as sensor networks, similarity search is more practical than exact match in stream processing, where both the queries and the data items are always change over time. The volumes of multi-streams could be very large, since new items are continuously appended. The main idea is to build a small size of synopsis instead of keeping original streams by using our proposed tec...

The present work was planned to evaluate the phytoextraction of metal mine tailings, Sarcheshmeh copper mine, SE of Iran, by the endemic plant species Medicago sativa L. (Alfalfa). In this pot experiment, we investigated the effects of seven amendments on the growth of alfalfa and uptaking metals from the mine tailings and stream sediment of tailing dam surface. The mean metal concentrations in...