Cognitive radio (CR) technology enables the opportunistic use of the vacant licensed frequency bands and henceforth improving the spectrum utilization. Cognitive radio networks (CRNs) are composed of cognitive, spectrum-agile devices which are capable of changing their configurations depending upon the spectral environment which they use. This capability opens up the possibility of designing flexible and dynamic spectrum access strategies with the purpose of opportunistically reusing portions of the spectrum temporarily vacated by licensed primary users. On the other hand, the flexibility in the spectrum access phase comes with an increased complexity in the design of communication protocols at different layers. An extensive overview of the research in the field of routing for Cognitive radio networks differentiating the two main categories:  approaches based on a full spectrum knowledge, and approaches that consider only local spectrum knowledge obtained via distributed procedures and protocols is been provided in this report.

It is generally desired to have a wireless sensor network (WSN) that will run on little power (if possible, none at all) thereby saving cost, and the inconveniences of having to replace batteries in some difficult to access areas of usage. Despite several researches on WSN energy consumption, there is no clear transceiver energy consumption model to use when designing very low power WSN. By studying the energy consumption map of the transceiver of a WSN node in different states and within state transitions, we propose in this paper the energy consumption model of the transceiver unit of a typical sensor node. The contribution of this paper is an innovative energy consumption model based on finite automata which reveals the relationship between the aggregate energy consumption and power characteristics of the transceiver components.

Keywords- Transceiver energy model, Low power Wireless Sensor Networks.

Traffic congestion occurs inevitably in aggregated channel when access networks connect to transport network over a bottleneck data transmission link. The reason of congestion is a lack of bandwidth and continuously customer requirements growth in transmission rate to network content. In this article is investigated influence of data transmission link parameters, as an available bandwidth and packet transmission delay, to queue discipline processing in access router. Fuzzy logic controller (FLC) is considered as an active queue management discipline processing with explicit congestion notification (ECN). Traffic congestion is simulated in a bottleneck link between two routers in Network simulator-2 (NS-2) software. Queue discipline processing was estimated by calculation the quality of service indicators: packets loss, average packet delay and packet delay variation. Statistical analysis of simulation result have given the possibility to define dependence between the quality of service indicators and the data link parameters applicable to considered queue discipline.

Keywords:
Active queue management, congestion avoidance, fuzzy logic, FLC, network simulator, NS-2, TCP/IP.

Ambient Intelligence refers to an environment that is sensitive, adaptive, and responsive to the presence of people. Such an environment relies heavily on information from the numerous sensors monitoring the environment. The components of the ambient intelligence environment is pervasive, meaning all devices are connected to the personal, local, regional, national, and global network. The devices are also invisible, until they are needed.

Keywords— Ambient Intelligence, Intelligent Product, Cooperation, Security, WSN, Petri Nets, Castalia