RTDSR protocol for channel attacks prevention in mobile ad hoc ambient intelligence home networks

In ambient intelligence home networks, attacks can be on the home devices or the communication channel. This paper focuses on the channel attacks prevention by proposing Real Time Dynamic Source Routing (RTDSR) protocol. The protocol adopted the observation based cooperation enforcement in ad hoc networks (oceans) and collaborative reputation mechanism built on Dynamic Source Routing (DSR) protocol. The RTDSR introduced lookup table on the source, destination and intermediate nodes. It also ensures that data path with high reputation are used for data routing and a monitoring watchdog was introduced to ensure that the next node forward the packet properly. The RTDSR protocol was simulated and benchmarked with DSR protocol considering network throughput, average delay, routing overhead and response time as performance metrics. Simulation result revealed a better performance of RTDSR protocol over existing DSR protocol.Keywords: RTDSR, Ambient, Home network, Channel attacks, Protocol, Packet, OPNE

An Improved Computational Model for Adaptive Communication Channel Estimation

Channel estimation is an important and necessary function performed by modern wireless receivers. The goal of channel estimation is to measure the effects of the channel on known or partially known transmission. The usual practice in acquiring knowledge about a channel is to model the channel and then acquire the parameters involved in the model. This paper proposes a variable partial update model for adaptive communication channel estimation with a view to improving signal error at the receiver station. The proposed model is composed of finite impulse response transversal adaptive filter and least mean square adaptation algorithm. The performance of the proposed model was compared with the full update model. The evaluation results indicated that the proposed model performed better than the full update model in terms of computational complexity, memory load, and convergence rate

An ontology-based information retrieval mechanism for E-learning management system

During the last decade, increasing attention has been focused on ontologies and Ontological Engineering. The application of ontological engineering technique to e-learning, though still in its early stage, has become a phenomena tool in the integration and adaptation of a dynamic and flexible elearning environment, where tutors and learners are provided with the functionality of personalizing their learning process, this has not fully considered the generality of an entire field of study. This paper presents an ontology-based framework for classification of the entire courses of computer science at the university level. A model of an e-learning domain in the context of material classification that enables students retrieve information about a particular course in personalized ways was presented the method adopted elicited e-learning knowledge using documented materials, observation, consultation, prototyping among others. With domain expertise developed, the knowledge elicited was analyzed and formally represented using OWL-Description Logic. The design was implemented using Protégé 5.0 editor. The validation for accuracy and completeness was carried out with the domain and ontology experts using consistency checking reasoned, DL-Query. The results of the implementation show that elearning materials can be searched and retrieved easily and timely. The study also established and formalised an effective computational approach for representing information content of educational resources thereby helping to improve the flexibility of content representation in an e-learning system.Keywords: e-learning, Ontological Engineering, Ontology, Ontology Web Language (OWL), Knowledge Management, Description LogicVol. 26, No 1, June 201