Social and environmental regulation of signal plasticity and signal reliability in the electric fish Brachyhypopomus gauderio

The balance between the costs and benefits of conspicuous signals ensures that the expression of those signals is related to the quality of the bearer. Plastic signals could enable males to maximize conspicuous traits to impress mates and competitors, but reduce the expression of those traits to minimize signaling costs, potentially compromising the information conveyed by the signals. ^ I investigated the effect of signal enhancement on the information coded by the biphasic electric signal pulse of the gymnotiform fish Brachyhypopomus gauderio. Increases in population density drive males to enhance the amplitude of their signals. I found that signal amplitude enhancement improves the information about the signaler's size. Furthermore, I found that the elongation of the signal's second phase conveys information about androgen levels in both sexes, gonad size in males and estrogen levels in females. Androgens link the duration of the signal's second phase to other androgen-mediated traits making the signal an honest indicator of reproductive state and aggressive motivation. ^ Signal amplitude enhancement facilitates the assessment of the signaler's resource holding potential, important for male-male interactions, while signal duration provides information about aggressive motivation to same-sex competitors and reproductive state to the opposite sex. Moreover, I found that female signals also change in accordance to the social environment. Females also increase the amplitude of their signal when population density increases and elongate the duration of their signal's second phase when the sex ratio becomes female-biased. Indicating that some degree of sexual selection operates in females. ^ I studied whether male B. gauderio use signal plasticity to reduce the cost of reproductive signaling when energy is limited. Surprisingly, I found that food limitation promotes the investment in reproduction manifested as signal enhancement and elevated androgen levels. The short lifespan and single breeding season of B. gauderio diminishes the advantage of energy savings and gives priority to sustaining reproduction. I conclude that the electric signal of B. gauderio provides reliable information about the signaler, the quality of this information is reinforced rather than degraded with signal enhancement.^

Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.