Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks

With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.

Ecological and social drivers of coffee pollination in Santander, Colombia

Bees and other insects provide pollination services that are key to determining the fruit set on coffee plantations. These pollination services are influenced by local ecology as well as human factors, both social and economic. To better understand these different factors, we assessed their effect on pollinators and coffee pollination services in Santander, Colombia. We quantified the effect of key ecological drivers on pollinator community composition, such as the method of farm management (either conventional or organic) and the surrounding landscape composition, specifically the proximity to forest. We found that ambient levels of pollination services provided by the local pollinator fauna (open pollination) accounted for a 10.5 ± 2.0% increase in final coffee fruit set, and that the various pollinators are affected differently by the differing factors. For example, our findings indicate that conventional farm management, using synthetic inputs, can promote pollinators, especially if they are in close proximity to natural forest fragments. This is particularly true for stingless bees. Honeybee visitation to coffee is also positively influenced by the conventional management of farms. Factors associated with greater numbers of stingless bees on farms include greater shade cover, lower tree densities, smaller numbers and types of trees in bloom, and younger coffee plantations. A forested landscape close to farms appears to enhance these factors, giving increased stability and resilience to the pollinating bees and insects. However we found that organic farms also support diverse pollinator communities, even if distant from forest fragments. The contribution of honeybees to pollination value (US$129.6/ha of coffee) is greater than that of stingless bees (US$16.5/ha of coffee). Since the method of farm management has a major impact on the numbers and types of pollinators attracted to farms, we have analysed the statistically significant social factors that influence farmers’ decisions on whether to adopt organic or conventional practices. These include the availability of technology, the type of landowner (whether married couples or individual owners), the number of years of farmers’ formal education, the role of institutions, membership of community organizations, farm size, coffee productivity and the number of coffee plots per farm. It is hoped that the use of our holistic approach, which combines investigation of the social as well as the ecological drivers of pollination, will help provide evidence to underpin the development of best practices for integrating the management of pollination into sustainable agricultural practices.

Apple pollination: demand depends on variety and supply depends on pollinator identity

Insect pollination underpins apple production but the extent to which different pollinator guilds supply this service, particularly across different apple varieties, is unknown. Such information is essential if appropriate orchard management practices are to be targeted and proportional to the potential benefits pollinator species may provide. Here we use a novel combination of pollinator effectiveness assays (floral visit effectiveness), orchard field surveys (flower visitation rate) and pollinator dependence manipulations (pollinator exclusion experiments) to quantify the supply of pollination services provided by four different pollinator guilds to the production of four commercial varieties of apple. We show that not all pollinators are equally effective at pollinating apples, with hoverflies being less effective than solitary bees and bumblebees, and the relative abundance of different pollinator guilds visiting apple flowers of different varieties varies significantly. Based on this, the taxa specific economic benefits to UK apple production have been established. The contribution of insect pollinators to the economic output in all varieties was estimated to be £92.1M across the UK, with contributions varying widely across taxa: solitary bees (£51.4M), honeybees (£21.4M), bumblebees (£18.6M) and hoverflies (£0.7M). This research highlights the differences in the economic benefits of four insect pollinator guilds to four major apple varieties in the UK. This information is essential to underpin appropriate investment in pollination services management and provides a model that can be used in other entomolophilous crops to improve our understanding of crop pollination ecology.