We consider the traffic adaptive channel allocation problem in long-distance 802.11 mesh networks. Our approach is to exploit the capability provided by 802.11 hardware to use different channel widths and assign channel widths to links based on their relative traffic volume. We show that this traffic-aware channel width assignment problem is NP-complete and propose a polynomial time, greedy channel allocation algorithm that guarantees valid channel allocations for each node. Evaluation of the proposed algorithm via simulations of real network topologies shows that it consistently outperforms the current approach of fixed width allocation due to its ability to adapt to spatio-temporal variations in traffic demands.

We consider the distributed channel allocation problem in IEEE 802.11-based multi-radio wireless mesh networks. We develop a new scalable protocol termed LCAP for efficient and adaptive distributed multi-radio channel allocation. In LCAP, nodes autonomously learn their channel allocation based on neighborhood and channel usage information, which is obtained via a novel neighbor discovery protocol that enables neighboring nodes to efficiently discover each other even when they do not share a common channel. Extensive simulation-based evaluation of LCAP relative to the state-of-the-art Asynchronous Distributed Coloring (ADC) protocol demonstrates that LCAP is able to achieve its stated objectives of efficient channel utilization across diverse traffic patterns, protocol scalability and adaptivity to factors such as external interference. We also present a prototype implementation of the LCAP neighbor discovery module that is key to implementing the proposed approach.

Online Curriculum Portals aim to support networks of instructors and learners by providing a space of convergence for enhancing peer-to-peer learning interactions among individuals of an educational institution. To this end, effective, open and scalable e-learning systems are required to acquire, store, and share knowledge under the form of learning objects (LO). In this paper, we are interested in exploiting the semantic relationships that characterize these LOs (e.g., prerequisite, part-of or see-also) in order to capture and access individual and group knowledge in conjunction with the learning processes supported by educational institutions. To achieve this functionality, Semantic Web (e.g., RDF/s) and declarative query languages (e.g., RQL) are employed to represent LOs and their relationships (e.g., LOM), as well as, to support navigation at the conceptual e-learning Portal space. In this way, different LOs could be presented to the same learners, according to the traversed schema navigation paths (i.e., learning paths). Using the Apache Jetspeed framework we are able to generate and assemble at run-time portlets (i.e., pluggable web components) for visualizing personalized views as dynamic web pages. Last but not least, both learners and instructors can employ the same Portal GUI for updating semantically described LOs and thus support an open-ended continuum of learning. To the best of our knowledge, the work presented in this paper is the first Online Curriculum Portal platform supporting the aforementioned functionality.