MOSDEN: An Internet of Things Middleware for Resource Constrained Mobile Devices

The Internet of Things (IoT) is part of Future Internet and will comprise many billions of Internet Connected Objects (ICO) or `things' where things can sense, communicate, compute and potentially actuate as well as have intelligence, multi-modal interfaces, physical/ virtual identities and attributes. Collecting data from these objects is an important task as it allows software systems to understand the environment better. Many different hardware devices may involve in the process of collecting and uploading sensor data to the cloud where complex processing can occur. Further, we cannot expect all these objects to be connected to the computers due to technical and economical reasons. Therefore, we should be able to utilize resource constrained devices to collect data from these ICOs. On the other hand, it is critical to process the collected sensor data before sending them to the cloud to make sure the sustainability of the infrastructure due to energy constraints. This requires to move the sensor data processing tasks towards the resource constrained computational devices (e.g. mobile phones). In this paper, we propose Mobile Sensor Data Processing Engine (MOSDEN), an plug-in-based IoT middleware for mobile devices, that allows to collect and process sensor data without programming efforts. Our architecture also supports sensing as a service model. We present the results of the evaluations that demonstrate its suitability towards real world deployments. Our proposed middleware is built on Android platform

MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications

Mobile smartphones along with embedded sensors have become an efficient enabler for various mobile applications including opportunistic sensing. The hi-tech advances in smartphones are opening up a world of possibilities. This paper proposes a mobile collaborative platform called MOSDEN that enables and supports opportunistic sensing at run time. MOSDEN captures and shares sensor data across multiple apps, smartphones and users. MOSDEN supports the emerging trend of separating sensors from application-specific processing, storing and sharing. MOSDEN promotes reuse and re-purposing of sensor data hence reducing the efforts in developing novel opportunistic sensing applications. MOSDEN has been implemented on Android-based smartphones and tablets. Experimental evaluations validate the scalability and energy efficiency of MOSDEN and its suitability towards real world applications. The results of evaluation and lessons learned are presented and discussed in this paper.Comment: Accepted to be published in Transactions on Collaborative Computing, 2014. arXiv admin note: substantial text overlap with arXiv:1310.405

Preference rules for label ranking: Mining patterns in multi-target relations

In this paper, we investigate two variants of association rules for preference data, Label Ranking Association Rules and Pairwise Association Rules. Label Ranking Association Rules (LRAR) are the equivalent of Class Association Rules (CAR) for the Label Ranking task. In CAR, the consequent is a single class, to which the example is expected to belong to. In LRAR, the consequent is a ranking of the labels. The generation of LRAR requires special support and confidence measures to assess the similarity of rankings. In this work, we carry out a sensitivity analysis of these similarity-based measures. We want to understand which datasets benefit more from such measures and which parameters have more influence in the accuracy of the model. Furthermore, we propose an alternative type of rules, the Pairwise Association Rules (PAR), which are defined as association rules with a set of pairwise preferences in the consequent. While PAR can be used both as descriptive and predictive models, they are essentially descriptive models. Experimental results show the potential of both approaches.This research has received funding from the ECSEL Joint Undertaking, the framework programme for research and innovation horizon 2020 (2014-2020) under grant agreement number 662189-MANTIS-2014-1, and by National Funds through the FCT — Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013

Discovering a taste for the unusual: exceptional models for preference mining

Exceptional preferences mining (EPM) is a crossover between two subfields of data mining: local pattern mining and preference learning. EPM can be seen as a local pattern mining task that finds subsets of observations where some preference relations between labels significantly deviate from the norm. It is a variant of subgroup discovery, with rankings of labels as the target concept. We employ several quality measures that highlight subgroups featuring exceptional preferences, where the focus of what constitutes exceptional' varies with the quality measure: two measures look for exceptional overall ranking behavior, one measure indicates whether a particular label stands out from the rest, and a fourth measure highlights subgroups with unusual pairwise label ranking behavior. We explore a few datasets and compare with existing techniques. The results confirm that the new task EPM can deliver interesting knowledge.This research has received funding from the ECSEL Joint Undertaking, the framework programme for research and innovation Horizon 2020 (2014-2020) under Grant Agreement Number 662189-MANTIS-2014-1

The Chittagong story: studies on the ecology of rat floods and bamboo masting

Rodent population outbreaks due to the 50-year cycle of gregarious flowering and seed masting of Melocanna baccifera were first noted in the Chittagong Hill Tracts (CHT) of Bangladesh during the crop production cycle of 2008. The wave of flowering has steadily moved southward through the region each year, with seed masting still occurring in some areas of the CHT during 2010. Because of a lack of surveillance, it is not yet known whether all Melocanna bamboo forests across the region have now initiated flowering. Ecological surveys carried out during the masting event have provided some preliminary evidence that nearly all rodent species are able to exploit Melocanna bamboo seeds as a food resource, with nearly 30% of the seed fallen in forests damaged by rodents. Breeding potential of the predominant species found, Rattus rattus, appears to confirm that aseasonal breeding occurs due to the abundant supply of bamboo seed during masting events. These preliminary results obtained from ongoing research surveys are discussed in the context of the management response to the regional famine triggered by the severe crop damage caused by rodent population outbreaks

The Archaeology of Sulawesi

The central Indonesian island of Sulawesi has recently been hitting headlines with respect to its archaeology. It contains some of the oldest directly dated rock art in the world, and some of the oldest evidence for a hominin presence beyond the southeastern limits of the Ice Age Asian continent. In this volume, scholars from Indonesia and Australia come together to present their research findings and views on a broad range of topics. From early periods, these include observations on Ice Age climate, life in caves and open sites, rock art, and the animals that humans exploited and lived alongside. The archaeology presented from later periods covers the rise of the Bugis kingdom, Chinese trade ceramics, and a range of site-based and regional topics from the Neolithic through to the arrival of Islam. This carefully edited volume is the first to be devoted entirely to the archaeology of the island of Sulawesi, and it lays down a baseline for significant future research. Peter Bellwood, Emeritus Professor, The Australian National Universit

Heads I Win, Tails You Lose: Uncertainty and the Protection of Biodiversity from Invasive Alien Species

Scientists anticipate that the problem of invasive alien species will be exacerbated by co-stressors of biodiversity, such as, land clearing and climate change. One of the most effective means of regulating invasive alien species is to prevent their entry by implementing rigorous quarantine measures with strong border controls. Yet, regulators face constant uncertainty and the need to navigate a range of opinions on how best to deal with uncertainty. These difficulties are illustrated by the differing approaches to uncertainty embodied by the World Trade Organization on the one hand and the Convention on Biological Diversity on the other. While the former emphasises the need for overcoming uncertainty the latter also accommodates the need to manage uncertainty. This paper explores the impasse resulting from these strategies and also analyses whether Australia's Weed Risk Assessment provides a potential solution. It is argued that the Weed Risk Assessment can establish 'plausible hypotheses' that channel into the precautionary approach, giving regulators the flexibility of managing uncertainty by implementing measures without the benefit of full and conclusive scientific evidence. What is not clear, however, is whether the information-based processes of the Weed Risk Assessment will satisfy the scientific certainty requirements of the World Trade Organization

Domesticating Lebeckia ambigua: Solving the rhizobia issues.

Permanent dryland pastures are under-utilised in southern Australia (Angus and Peoples 2012), possibly due to the lack of well adapted perennial legume species that can fit into current farming systems. Lebeckia ambigua has been proposed as a candidate to fill this void with its adaptability to drought, acidic and infertile soils in low rainfall areas (Howieson et al. 2013). The research on L. ambigua has so far focussed on deep, sandy soils where cropping is problematic. Increasing the soil fertility in these previously low-profitable regions could provide mixed farming production with a comparative advantage over continuous cropping (Angus and Peoples 2012). However, the successful incorporation of L. ambigua into an agricultural system will require an understanding of its symbiont, Burkholderia species. Although L. ambigua and Burkholderia spp. have only recently been identified for domestication into agriculture (Howieson et al. 2013), researchers have had success with cultivating them throughout southern Western Australia (WA), except with inoculation. There is a challenge to keep the inoculant B. spp. alive, in a peat carrier, when coated onto L. ambigua seed for sowing in a drying environment. Clay granules, as an alternative carrier, have previously been shown to be unable to carry high numbers of cells of B. spp. (Howieson et al. 2013). Field experiments with amended clay granules carrying B. spp. produced nodules on L. ambigua, albeit not in large number. Attempts at quantifying the numbers of cells in the amended granules, by resuscitating B. spp. from them using antibiotic media and plant infection techniques, were unsuccessful. However, antibiotic profiling of B. spp. strains identified chloramphenicol (20μg/ml) in YMA as an excellent media to suppress contaminants in the clay to facilitate enumeration. Recently recovered strains of B. spp. were assessed alongside previous strains for tolerance to desiccation, which gave rise to a set of possible strains that could surpass the commonly used strain in this regard (WSM4204). Although clay granules were indicated to hold B. spp. cells sufficient for nodulation in the field, further studies must focus on the optimisation of a suitable inoculant technology for L. ambigua. The B. spp. and strain differences in tolerance to desiccation identified in this work may assist this target