Proactive Location-Based Scheduling of Delay-Constrained Traffic Over Fading Channels

In this paper, proactive resource allocation based on user location for point-to-point communication over fading channels is introduced, whereby the source must transmit a packet when the user requests it within a deadline of a single time slot. We introduce a prediction model in which the source predicts the request arrival $T_p$ slots ahead, where $T_p$ denotes the prediction window (PW) size. The source allocates energy to transmit some bits proactively for each time slot of the PW with the objective of reducing the transmission energy over the non-predictive case. The requests are predicted based on the user location utilizing the prior statistics about the user requests at each location. We also assume that the prediction is not perfect. We propose proactive scheduling policies to minimize the expected energy consumption required to transmit the requested packets under two different assumptions on the channel state information at the source. In the first scenario, offline scheduling, we assume the channel states are known a-priori at the source at the beginning of the PW. In the second scenario, online scheduling, it is assumed that the source has causal knowledge of the channel state. Numerical results are presented showing the gains achieved by using proactive scheduling policies compared with classical (reactive) networks. Simulation results also show that increasing the PW size leads to a significant reduction in the consumed transmission energy even with imperfect prediction.Comment: Conference: VTC2016-Fall, At Montreal-Canad

Improving location prediction services for new users with probabilistic latent semantic analysis

Location prediction systems that attempt to determine the mobility patterns of individuals in their daily lives have become increasingly common in recent years. Approaches to this prediction task include eigenvalue decomposition [5], non-linear time series analysis of arrival times [10], and variable order Markov models [1]. However, these approachesall assume sufficient sets of training data. For new users, by definition, this data is typically not available, leading to poor predictive performance. Given that mobility is a highly personal behaviour, this represents a significant barrier to entry. Against this background, we present a novel framework to enhance prediction using information about the mobility habits of existing users. At the core of the framework is a hierarchical Bayesian model, a type of probabilistic semantic analysis [7], representing the intuition that the temporal features of the new user’s location habits are likely to be similar to those of an existing user in the system. We evaluate this framework on the real life location habits of 38 users in the Nokia Lausanne dataset, showing that accuracy is improved by 16%, relative to the state of the art, when predicting the next location of new users

Habitat selection

Habitat selection is the behavioural process determining the distribution of individuals among habitats varying in quality, thus affecting individual fitness and population growth. Models of population dynamics often assume that individuals have perfect knowledge about habitat qualities and settle accordingly in the best habitats available. Many studies of dispersal have focused on the movements of individuals away from a site, but knowledge on settlement decisions is still scarce. I investigated settlement and departure decisions in a long-distant migrant, the northern wheatear (Oenanthe oenanthe), breeding in a heterogeneous agricultural landscape. First, I investigated the settlement of wheatears choosing a new territory at the time of territory establishment in spring. I show that territory selection is non-ideal as wheatears did not prefer territories with characteristics most closely predicting individual fitness. Second, I studied the territory selection of experienced breeders which may use many potential cues as they have been breeding in the same area before. The results show that information gathering of experienced breeders is constrained, and that they cannot always settle at a preferred site probably because of the earlier establishment by other individuals. Third, I show that such a priority constraint in territory site selection may be a proximate cause for female-biased dispersal in wheatears and possibly in many other bird species. Fourth, as a first step to link habitat selection behaviour and population dynamics, I investigated habitat-specific population growth. Overall, I show that constraints acting on individual habitat selection result in a greater proportion of individuals breeding in poorer habitats than would be expected from ideal selection, which has consequences for population persistence

Phenology of the Diamondback moth (Plutella xylostella) in the UK and provision of decision support for brassica growers

In the UK, severe infestations by Plutella xylostella occur sporadically and are due mainly to the immigration of moths. The aim of this study was to develop a more detailed understanding of the phenology of P. xylostella in the UK and investigate methods of monitoring moth activity, with the aim of providing warnings to growers. Plutella xylostella was monitored using pheromone traps, by counting immature stages on plants, and by accessing citizen science data (records of sightings of moths) from websites and Twitter. The likely origin of migrant moths was investigated by analysing historical weather data. The study confirmed that P. xylostella is a sporadic but important pest, and that very large numbers of moths can arrive suddenly, most often in early summer. Their immediate sources are countries in the western part of continental Europe. A network of pheromone traps, each containing a small camera sending images to a website, to monitor P. xylostella remotely provided accessible and timely information, but the particular system tested did not appear to catch many moths. In another approach, sightings by citizen scientists were summarised on a web page. These were accessed regularly by growers and, at present, this approach appears to be the most effective way of providing timely warnings

Rapid changes in phenotype distribution during range expansion in a migratory bird

The capacity of species to track changing environmental conditions is a key component of population and range changes in response to environmental change. High levels of local adaptation may constrain expansion into new locations, while the relative fitness of dispersing individuals will influence subsequent population growth. However, opportunities to explore such processes are rare, particularly at scales relevant to species-based conservation strategies. Icelandic black-tailed godwits, Limosa limosa islandica, have expanded their range throughout Iceland over the last century. We show that current male morphology varies strongly in relation to the timing of colonization across Iceland, with small males being absent from recently occupied areas. Smaller males are also proportionately more abundant on habitats and sites with higher breeding success and relative abundance of females. This population-wide spatial structuring of male morphology is most likely to result from female preferences for small males and better-quality habitats increasing both small-male fitness and the dispersal probability of larger males into poorer-quality habitats. Such eco-evolutionary feedbacks may be a key driver of rates of population growth and range expansion and contraction