The next major advance in the Web?Web 3.0?will be built on semantic Web technologies, which will allow data to be shared and reused across application, enterprise, and community boundaries. Written by a team of highly experienced Web developers, this book explains examines how this powerful new technology can unify and fully leverage the ever-growing data, information, and services that are available on the Internet. Helpful examples demonstrate how to use the semantic Web to solve practical, real-world problems while you take a look at the set of design principles, collaborative working groups, and technologies that form the semantic Web. The companion Web site features full code, as well as a reference section, a FAQ section, a discussion forum, and a semantic blog.

Technological advances in miniaturization and wireless networking have enabled the utilization of distributed wireless sensor networks (WSN) in many applications. WSNs often use clustering as a means of achieving scalable and efficient communications. Cluster head nodes are of increased importance in these network topologies because they are both communication and coordination hubs. Much of the research into maximizing WSN longevity and efficiency focuses on dynamically clustering the network according to the residual energy contained within each node. This is a result of the commonly held assumption that battery depletion is the primary cause of node failure. In this work, we consider that there are applications in which threats may significantly impact node survival. In order to cope with these applications, we present a threat-aware clustering algorithm, extending the Hybrid Energy Efficient Distributed clustering algorithm (HEED) that minimizes the exposure of cluster heads to threats in the network environment. Simulation results indicate that our extended threat-aware HEED, or t-HEED, improves both the longevity and energy efficiency of a WSN while incurring minimal additional overhead. Our research demonstrates and motivates the need for a general framework for adaptive context-aware clustering in WSNs.

In our experiences building systems that use Semantic Web technologies, we have often identified a requirement for a consistent way to associate data values with standard units. We have tried a number of solutions to this issue, each of which has its own benefits and drawbacks in terms of complexity, expressivity, and clarity. In this paper, we present a discussion of the issue and a proposal for a simple extension to OWL/RDF to support the annotation of literal values with standard SI units that meets our needs without introducing many of the drawbacks of alternate approaches.

We propose a method to manage transmission power in nodes belonging to a wireless sensor network (WSN). The scenario contemplates uncoordinated communications using impulse radio ultra wideband (IR-UWB). Transmission power is controlled according to the statistical nature of the multiple access interference (MAI) produced by the nodes in the close vicinity of the communicating nodes. The statistical nature of the MAI is a function of the node population density within the area of coverage of the WSN. We show that when the node population density is high enough transmission power savings are possible.