Bee System Based Base Station Cooperation Technique for Mobile Cellular Networks

Wireless Personal Communications - Mobility with high degree of network-facility is a mandatory attribute for better QoS in cellular networks, but it leads to a huge increment in energy...     

Design of plasmonic half-adder and half-subtractor circuits employing nonlinear effect in Mach–Zehnder interferometer

Plasmonic metal–insulator–metal (MIM) waveguides have the unique attribute of propagating surface plasmons beyond the diffraction limit. In this paper, basic designs for half-adder and half-subtractor circuits are proposed based on the nonlinear effect in Mach–Zehnder interferometers designed using plasmonic MIM waveguides. The proposed devices are studied in the third optical communications window with transverse magnetic polarization. The designs are verified by the finite-difference time-domain technique with the help of MATLAB simulations.     

Evaluating and improving adaptive educational systems with learning curves

Personalised environments such as adaptive educational systems can be evaluated and compared using performance curves. Such summative studies are useful for determining whether or not new modifications enhance or degrade performance. Performance curves also have the potential to be utilised in formative studies that can shape adaptive model design at a much finer level of granularity. We describe the use of learning curves for evaluating personalised educational systems and outline some of the potential pitfalls and how they may be overcome. We then describe three studies in which we demonstrate how learning curves can be used to drive changes in the user model. First, we show how using learning curves for subsets of the domain model can yield insight into the appropriateness of the model’s structure. In the second study we use this method to experiment with model granularity. Finally, we use learning curves to analyse a large volume of user data to explore the feasibility of using them as a reliable method for fine-tuning a system’s model. The results of these experiments demonstrate the successful use of performance curves in formative studies of adaptive educational systems.     

A Game Theory Based Multi Layered Intrusion Detection Framework for Wireless Sensor Networks

Most of the existing intrusion detection frameworks proposed for wireless sensor networks (WSNs) are computation and energy intensive, which adversely affect the overall lifetime of the WSNs. In addition, some of these frameworks generate a significant volume of IDS traffic, which can cause congestion in bandwidth constrained WSNs. In this paper, we aim to address these issues by proposing a game theory based multi layered intrusion detection framework for WSNs. The proposed framework uses a combination of specification rules and a lightweight neural network based anomaly detection module to identify the malicious sensor nodes. Additionally, the framework models the interaction between the IDS and the sensor node being monitored as a two player non-cooperative Bayesian game. This allows the IDS to adopt probabilistic monitoring strategies based on the Bayesian Nash Equilibrium of the game and thereby, reduce the volume of IDS traffic introduced into the sensor network. The framework also proposes two different reputation update and expulsion mechanisms to enforce cooperation and discourage malicious behavior among monitoring nodes. These mechanisms are based on two different methodologies namely, Shapley Value and Vickery–Clark–Grooves (VCG) mechanism. The complexity analysis of the proposed reputation update and expulsion mechanisms have been carried out and are shown to be linear in terms of the input sizes of the mechanisms. Simulation results show that the proposed framework achieves higher accuracy and detection rate across wide range of attacks, while at the same time minimizes the overall energy consumption and volume of IDS traffic in the WSN.     

Highly‐Cyclable Room‐Temperature Phosphorene Polymer Electrolyte Composites for Li Metal Batteries

Despite significant interest toward solid‐state electrolytes owing to their superior safety in comparison to liquid‐based electrolytes, sluggish ion diffusion and high interfacial resistance limit their application in durable and high‐power density batteries. Here, a novel quasi‐solid Li⁺ ion conductive nanocomposite polymer electrolyte containing black phosphorous (BP) nanosheets is reported. The developed electrolyte is successfully cycled against Li metal (over 550 h cycling) at 1 mA cm^?2 at room temperature. The cycling overpotential is dropped by 75% in comparison to BP‐free polymer composite electrolyte indicating lower interfacial resistance at the electrode/electrolyte interfaces. Molecular dynamics simulations reveal that the coordination number of Li⁺ ions around (trifluoromethanesulfonyl)imide (TFSI^?) pairs and ethylene‐oxide chains decreases at the Li metal/electrolyte interface, which facilitates the Li⁺ transport through the polymer host. Density functional theory calculations confirm that the adsorption of the LiTFSI molecules at the BP surface leads to the weakening of N and Li atomic bonding and enhances the dissociation of Li⁺ ions. This work offers a new potential mechanism to tune the bulk and interfacial ionic conductivity of solid‐state electrolytes that may lead to a new generation of lithium polymer batteries with high ionic conduction kinetics and stable long‐life cycling.