Starting from 1990s and until now, Grid computing has been mainly used in scientific laboratories. Only in the last few years, it is evolving into a business-innovating technology that is driving commercial adoption. In this paper, we describe GridVideo, a Grid-based multimedia application for the distributed tailoring and streaming of media files. The objective is to show, starting from a real experience, how Grid technologies can be used for the development of nonscientific applications. Relevant performance aspects are analyzed, regarding both user-oriented (in terms of responsiveness) and provider-oriented (in terms of system efficiency) requirements. Different multimedia data dissemination strategies have been analyzed and an innovative technique, based on the Fibonacci series, is proposed. To respond to the stringent quality-of-service (QoS) requirements, typical of soft real-time applications, a reservation-based architecture is presented. Such architecture is able to manage the Grid resource allocation, thus enabling the provisioning of advanced services with different QoS levels. Technical and practical problems encountered during the development are discussed, and a thorough performance evaluation of the developed prototype is presented.

Providing an efficient localization system is one of the most important goals to be pursued if an efficient utilization of sensor networks has to be addressed. This paper proposes a novel localization system based on Kohonen 's self organizing maps (SOMs), able to provide some Artificial Intelligence features to sensor nodes. A SOM is a particular neural network that learns to classify data without any supervision. In each sensor node, a SOM is implemented to evaluate the sensor node position, using a very little amount of storage and computing resources. In a scenario where thousands of sensor nodes are placed, this system evaluates the position of each sensor in a distributed manner, assuming a very little percentage of nodes knowing their actual position.