Data streaming applications, usually composed of sequential/parallel data processing tasks organized as a workflow, bring new challenges to workflow scheduling and resource allocation in grid environments. Due to the high volumes of data and relatively limited storage capability, resource allocation and data streaming have to be storage aware. Also to improve system performance, the data stream...

a novel evolving fuzzy rule-based classifier, namely parsimonious classifier (pClass), is proposed in this paper. pClass can set off its learning process either from scratch with an empty rule base or from an initially trained fuzzy model. Importantly, pClass not only adopts the open structure concept, where an automatic knowledge building process can be cultivated during the training process, ...

In this paper we propose to approach the subject of Twitter Topic Detection when in the presence of a large number of trending topics. We use a new technique, called Twitter Topic Fuzzy Fingerprints, and compare it with two popular text classification techniques, Support Vector Machines (SVM) and k-Nearest Neighbours (kNN). Preliminary results show that it outperforms the other two techniques, ...

During the last decade, we witnessed a rapid growth in deployment of pull-based P2P streaming applications. In these applications, each node selects some other nodes as its neighbors and requests streaming data from them. This scheme allows eliminating data redundancy and recovering from data loss, but it pushes the complexity to the receiver node side. In this paper, we theoretically study the...

Distributed multimedia streaming systems are increasingly popular due to technological advances, and numerous streaming services are available today. On servers or proxy caches, there is a huge scaling challenge in supporting thousands of concurrent users that request delivery of high-rate, time-dependent data like audio and video, because this requires transfers of large amounts of data throug...

Data streaming applications, usually composed with sequential/parallel data processing tasks organized in a workflow manner, bring new challenges to workflow scheduling and resource allocation in grid environments. Due to high volumes of data and relatively limit storage capability, resource allocation and data streaming have to be storage aware. Also in order to improve system performance, dat...

Social media data are widely used to gain insights about social incidents, whether on a local or global scale. Within the process of analyzing and evaluating data, it is common practice download store locally. Considerations privacy protection users often neglected thereby. However, protecting when dealing with personal demanded by laws ethics. In this paper, we introduce method using cardinali...

One of the fundamental challenges facing the unprecedented data deluge produced by the sensor networks is how to manage time-series streaming data so that they can be reasoning-ready and provenance-aware. Semantic web technology shows great promise but lacks adequate support for the notion of time. We present a system for the representation, indexing and querying of time-series data, especially...