Traffic based energy consumption optimisation to improve the lifetime and performance of ad hoc wireless sensor networks

Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.

A lifetime of language experience at each click!

Native speakers learn their mother tongue slowly, from birth, by the constant repetition of common words and phrases in a variety of contexts and situations, within the language community. As foreign language learners, we face considerable disadvantages when compared to children learning their mother tongue. Foreign language learners start later in life, have less time, have fewer opportunities to experience the language, and learn in the restricted environment of the classroom. Teachers and books give us information about many words and phrases, but it is difficult for us to know what we need to focus on and learn thoroughly, and what is less important. The rules and explanations are often difficult for us to understand. A large language corpus represents roughly the amount and variety of language that a native-speaker experiences in a whole lifetime. Learners can now access language corpora. We can check which words and phrases are important, and quickly discover their common meanings, collocations, and structural patterns. It is easier to remember things that we find out ourselves, rather than things that teachers or books tell us. Each click on the computer keyboard can show us the same information in different ways, so we can understand it more easily. We can also get many more examples from a corpus. Teachers and native-speakers can also use corpora, to confirm and enhance their own knowledge of a language, and prepare exercises to guide their students. Each of us can learn at our own level and at our own speed.

Carrier lifetime and exciton saturation in a strain-balanced InGaAs/InAsP multiple-quantum-well

The bleaching of the n = 1 heavy-hole and light-hole exciton absorption has been studied at room temperature and zero bias in a strain-balanced InGaAs/InAsP multiple quantum well. Pump-probe spectroscopy was used to measure the decay of the light-hole absorption saturation, giving a hole lifetime of only 280 ps. As only 16 meV separates the light- and heavy-hole bands, the short escape time can be explained by thermalization between these bands followed by thermionic emission over the heavy-hole barrier. The saturation density was estimated to be 1 × 1016 cm-3; this is much lower than expected for tensile-strained wells where both heavy and light holes have large in-plane masses. © 1998 American Institute of Physics.

Network lifetime maximization with cross-layer design in wireless sensor networks

This paper investigates a cross-layer design approach for minimizing energy consumption and maximizing network lifetime (NL) of a multiple-source and single-sink (MSSS) WSN with energy constraints. The optimization problem for MSSS WSN can be formulated as a mixed integer convex optimization problem with the adoption of time division multiple access (TDMA) in medium access control (MAC) layer, and it becomes a convex problem by relaxing the integer constraint on time slots. Impacts of data rate, link access and routing are jointly taken into account in the optimization problem formulation. Both linear and planar network topologies are considered for NL maximization (NLM). With linear MSSS and planar single-source and single-sink (SSSS) topologies, we successfully use Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expressions of the optimal NL when all nodes are exhausted simultaneously. The problem for planar MSSS topology is more complicated, and a decomposition and combination (D&C) approach is proposed to compute suboptimal solutions. An analytical expression of the suboptimal NL is derived for a small scale planar network. To deal with larger scale planar network, an iterative algorithm is proposed for the D&C approach. Numerical results show that the upper-bounds of the network lifetime obtained by our proposed optimization models are tight. Important insights into the NL and benefits of cross-layer design for WSN NLM are obtained.

Placebo expectancy effects in the relationship between glucose and cognition

The present study investigated the extent of expectancy in the ability of glucose to affect cognitive performance. Using a within-subjects design, subjects (n 26) completed four experimental sessions (in counterbalanced order and after an initial practice session) during which they were given a 500 ml drink 30 min prior to completing a cognitive assessment battery. In addition, all subjects completed a baseline practice session during which they were given no drink. During two of the sessions, subjects were given a drink containing 50 g glucose and on the other two they were given a drink containing aspartame. A balanced placebo design was used, such that for half the sessions subjects were accurately informed as to the content of the drink (glucose or aspartame), whereas in the other two sessions they were misinformed as to the content of the drink. The task battery comprised a 6 min visual analogue of the Bakan vigilance task, an immediate verbal free-recall task, an immediate verbal recognition memory task and a measure of motor speed (two-finger tapping). Blood glucose and self-reported mood were also recorded at several time points during each session. Glucose administration was found to improve recognition memory times, in direct contrast to previous findings in the literature. Glucose administration also improved performance on the Bakan task (relative to the control drink), but only in sessions where subjects were informed that they would receive glucose and not when they were told that they would receive aspartame. There were no effects either of the nature of the drink or expectancy on the other measures. These results are interpreted in terms of there being some contribution of expectancy concerning the positive effects of glucose on cognition in studies which have not used an equi-sweet dose of aspartame as a control drink.

Placebo expectancy effect of consuming psychoactive beverages on cognition and mood

Energy drinks have become very popular over the past few years with over half the student population in colleges and universities consuming them at least once a month (Malinauskas et al., 2007). It has been reported that the most common reasons why students consume energy drinks are to maintain alertness, reduce symptoms of hangover, increase energy, to help with driving and to prevent sleepiness (Attila and Cakir, 2011; Malinauskas et al., 2007). Previous research has suggested that energy drinks enhance sensorimotor speed, behaviour, and reduce levels of fatigue (Alford et al., 2001; Horne and Reyner, 2001; Howard and Marczinski, 2010; Kennedy and Scholey, 2004; Smit et al., 2004). The two key ingredients found in energy drinks are caffeine and glucose which have been examined together and alone, which have indicated enhanced reaction times, improvement in both verbal memory and sustained attention and more recently there is evidence to show that expectancy may play a key role in predicting intentions of future consumption (Adan and serra-Grabulosa, 2010). According to Kirsch (1997) people have specific expectations when they consume psychoactive substances that trigger physiological and psychological reactions, which tend to be independent of the psychoactive substance ingested. The concept of expectancy effects can be unambiguous especially when the information provided to the participants prior to the experimental study is specific to a possible outcome response. This thesis investigated the extent of expectancy effect on cognition and mood when psychoactive drinks containing caffeine and glucose were consumed in comparison to non-psychoactive drinks. The investigation commenced with examining the independent effects of caffeine and glucose, followed by the combination of caffeine and glucose as an energy drink on mood and cognition. The investigation advanced by comparing drink presentation effects (i.e., consuming the experimental drink from a branded bottle versus from a glass) irrespective of drink content on mood and cognition. Finally, the investigation lead to exploring what factors may predict expectancy effects when participants’ consumed psychoactive drinks among healthy adults. This was done by applying the Theory of Planned Behaviour model (TPB) (Azjen, 1991) to explore the contribution of specific attitudes, subjective norms and perceived behavioural control to the extent of expectancy effects as well as to behavioural intention, with additional variables including; beliefs, habits, past-behaviour, selfidentity. Self-identity representing someone who drinks energy drinks regularly. The level of internal consistency for Cronbach’s alpha was conducted for each variable within the TPB model and for the additional variables included for test reliability. This thesis consisted of four studies, which found that consumption of caffeine and glucose independently and also in combination resulted in psychoactive effects on mood and cognition. Experiment 2 was the only study, which indicated an expectancy effect for immediate verbal recall task and the mood subscale tension. Conversely, for experiment 4 there was a reverse effect found for the immediate verbal recall task. However, there were significant expectancy and psychoactive effects found for mood subscales throughout the four studies. It was also found that the TPB model had two significant variables past-behaviour and self-identity predicted intentions suggesting that participants who regularly consume psychoactive beverages have salient beliefs about consuming psychoactive drinks and the TPB model can be utilised to predict their intentions. Furthermore, the Theory of planned behaviour model found that habit and self-identity significantly predicted participants’ expectancy effects on the vigour. Indicating consumers of energy drinks are familiar with expected outcome response. This model was unsuccessful in predicting expectancy response for cognitive performance. Thus, overall the findings from the four studies indicated that caffeine and glucose have cognitive enhancing properties, which also positively improve mood. However, expectancy effects have been identified for mood only, whereas the overall findings within this thesis were unable to identify significant predictors of expectancy effect and response.

Pre-existent expectancy effects in the relationship between caffeine and performance

The present study investigated the impact of pre-existent expectancy regarding the effects of the caffeine load of a drink and the perception of the caffeine content on subjective mood and vigilance performance. Caffeine deprived participants (N=25) were tested in four conditions (within subjects design), using a 2 × 2 design, with caffeine load and information regarding the caffeine content of the drink. In two sessions, they were given caffeinated coffee and in two were given decaffeinated coffee. Within these two conditions, on one occasion they were given accurate information about the drink and on the other they were given inaccurate information about the drink. Mood and vigilance performance were assessed post ingestion. Caffeine was found to enhance performance, but only when participants were accurately told they were receiving it. When decaffeinated coffee was given, performance was poorer, irrespective of expectancy. However, when caffeine was given, but participants were told it was decaffeinated coffee, performance was as poor as when no caffeine had been administered. There were no easily interpretable effects on mood. The pharmacological effects of caffeine appear to act synergistically with expectancy. © 2010.