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The results suggest that computer-assisted learning methods will be of greater help to students who do not find the traditional methods effective. Explorations of the factors behind this are a matter for future research.

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Bio-inspired ad hoc routing is an active area of research. The designers of these algorithms predominantly evaluate the performance of their protocols with the help of simulation studies. Such studies are mostly scenario and simulator specific and their results cannot be generalized to other scenarios and simulators. Therefore, we argue that mathematical tools should be utilized to develop a consistent, provable and compatible formal framework in order to provide an unbiased evaluation of Bio-inspired ad hoc routing protocols. Motivated by this requirement, in this paper, we develop a probabilistic performance evaluation framework that can be used to model the following key performance metrics of an ad hoc routing algorithm: (1) routing overhead, (2) route optimality, and (3) energy consumption. We utilize this framework to model a well known Bee-inspired routing protocol for ad hoc sensor networks, BeeSensor. We also show that the proposed framework is generic enough and can easily be adapted to even model a classical routing protocol, Ad Hoc on Demand Distance Vector (AODV). The modeled metrics of the two algorithms not only allow unbiased performance comparison but also provide interesting insights into the parameters governing the behavior of these routing protocols.

Nowadays, because of the unpredictable nature of sensor nodes, propagating sensory data raises significant research challenges in Wireless Sensor Networks (WSNs). Recently, different cluster-based solutions are designed for the improvement of network stability and lifetime, however, most of the energy efficient solutions are developed for homogeneous networks, and use only a distance parameter for the data communication. Although, some existing solutions attempted to improve the selection of next-hop based on energy factor, nevertheless, such solutions are unstable and lack a reducing data delivery interruption in overloaded links. The aim of our proposed solution is to develop Reliable Cluster-based Energy-aware Routing (RCER) protocol for heterogeneous WSN, which lengthen network lifetime and decreases routing cost. Our proposed RCER protocol make use of heterogeneity nodes with respect to their energy and comprises of two main phases; firstly, the network field is parted in geographical clusters to make the network more energy-efficient and secondly; RCER attempts optimum routing for improving the next-hop selection by considering residual-energy, hop-count and weighted value of Round Trip Time (RTT) factors. Moreover, based on computing the measurement of wireless links and nodes status, RCER restore routing paths and provides network reliability with improved data delivery performance. Simulation results demonstrate significant development of RCER protocol against their competing solutions.

We review harvested energy prediction schemes to be used in wireless sensor networks and explore the relative merits of landmark solutions. We propose enhancements to the well-known Profile-Energy (Pro-Energy) model, the so-called Improved Profile-Energy (IPro-Energy), and compare its performance with Accurate Solar Irradiance Prediction Model (ASIM), Pro-Energy, and Weather Conditioned Moving Average (WCMA). The performance metrics considered are the prediction accuracy and the execution time which measure the implementation complexity. In addition, the effectiveness of the considered models, when integrated in an energy management scheme, is also investigated in terms of the achieved throughput and the energy consumption. Both solar irradiance and wind power datasets are used for the evaluation study. Our results indicate that the proposed IPro-Energy scheme outperforms the other candidate models in terms of the prediction accuracy achieved by up to 78% for short term predictions and 50% for medium term prediction horizons. For long term predictions, its prediction accuracy is comparable to the Pro-Energy model but outperforms the other models by up to 64%. In addition, the IPro scheme is able to achieve the highest throughput when integrated in the developed energy management scheme. Finally, the ASIM scheme reports the smallest implementation complexity.

Energy efficiency and reliability are the two important requirements for mission-critical wireless sensor networks. In the context of sensor topology control for routing and dissemination, Connected Dominating Set (CDS) based techniques proposed in prior literature provide the most promising efficiency and reliability. In a CDS-based topology control technique, a backbone-comprising a set of highly connected nodes-is formed which allows communication between any arbitrary pair of nodes in the network. In this paper, we show that formation of a polygon in the network provides a reliable and energy-efficient topology. Based on this observation, we propose Poly, a novel topology construction protocol based on the idea of polygons. We compare the performance of Poly with three prominent CDS-based topology construction protocols namely CDS-Rule K, Energy-efficient CDS (EECDS) and A3. Our simulation results demonstrate that Poly performs consistently better in terms of message overhead and other selected metrics. We also model the reliability of Poly and compare it with other CDS-based techniques to show that it achieves better connectivity under highly dynamic network topologies.