Extend OWL: toward a clustering integration of collaborative ontologies and agents

In order to solve the problem of how to collaborate with foreign agents and ontologies, a restricted clustering integration approach is proposed. It differs from the traditional approaches in which web ontology language （OWL） is extended by adding some new collaborative interfaces （ i. e., agent-link and ontology-link） to it instead of owl： import. Syntaxes of the interface for foreign ontologies and foreign agents, respectively, and a meta-method of clustering integrated collaboration are discussed. The approach focuses on taking advantage of OWL itself to solve the collaborative problems, and it is feasible to track the contexts of newadded knowledge concerning ontological collaboration.

Joint Design of Clustering and In-cluster Data Route for Heterogeneous Wireless Sensor Networks

A heterogeneous wireless sensor network comprises a number of inexpensive energy constrained wireless sensor nodes which collect data from the sensing environment and transmit them toward the improved cluster head in a coordinated way. Employing clustering techniques in such networks can achieve balanced energy consumption of member nodes and prolong the network lifetimes.In classical clustering techniques, clustering and in-cluster data routes are usually separated into independent operations. Although separate considerations of these two issues simplify the system design, it is often the non-optimal lifetime expectancy for wireless sensor networks. This paper proposes an integral framework that integrates these two correlated items in an interactive entirety. For that,we develop the clustering problems using nonlinear programming. Evolution process of clustering is provided in simulations. Results show that our joint-design proposal reaches the near optimal match between member nodes and cluster heads.