From Sensor to Observation Web with Environmental Enablers in the Future Internet

This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)

An Agent-Based Collaborative Approach to Graphing Causal Maps for Situation Formulation

We provide a background discussion of group support systems (GSS) research into aiding strategic management processes. GSS support for strategic management has been primarily focused on qualitative analysis and the communication processes surrounding strategic planning. While fully developed in common decision-support systems, powerful simulation modeling and quantitative analytical tools have been difficult to integrate into GSS system configurations because they require increased cognitive load and expert modeling support, a central problem now addressed by collaboration engineering. A conceptual and functional bridge is needed to integrate the qualitative and quantitative approaches, reduce cognitive load, and provide modeling support that does not require experts. Acar’s analytical causal mapping is introduced as a structured method for situational formulation and analysis of unstructured strategic problems. This form of causal mapping includes specific processes and analytical approaches offering cognitive modeling support for problem formulation. Its computational capabilities provide support for Systems Thinking approaches in a system easy to learn and use. Using the methodological template of the design science paradigm, we contribute a prototype system for the development and simulation of causal maps that uses RePast 2.0, a Java agent-based modeling (ABM) and simulation library

Does Complex Hydrology Require Complex Water Quality Policy? NManager Simulations for Lake Rotorua

This paper examines six different approaches to nutrient management, and simulates the economic costs and environmental impacts associated with them using NManager, a partial equilibrium simulation model developed by Motu and NIWA, the National Institute for Water and Atmospheric Research. We focus on Lake Rotorua in the Bay of Plenty in New Zealand, where the regional council is concerned with the decline in the lake's water quality and has set a goal to restore the lake to its condition during the 1960s. Reaching this goal will require significant reductions in the amount of nutrients discharged into the lake, especially from non-point sources such as farm land. Managing water quality is made difficult by the presence of groundwater lags in the catchment: nutrients that leach from the soil arrive at the lake over multiple years. The mitigation schemes we consider are land retirement, requiring best practice, explicit nitrogen limits on landowners, a simple nutrient trading scheme, and two more complex trading schemes that account for groundwater lags. We demonstrate that best practice alone is not sufficient to meet the environmental target for Lake Rotorua. Under an export trading scheme, the distribution of mitigation across the catchment is more cost effective than its distribution under explicit limits on landowners or land retirement. However, the more complex trading schemes do not result in sufficient, or sufficiently certain, gains in cost effectiveness over the simple trading scheme to justify the increase in complexity involved in their implementation.groundwater, Lake Rotorua, model, nutrients, nutrient trading, water quality, non-point source pollution

The Effects of Interruption Relevance and Complexity on Primary Task Resumption and Mental Demand

In the present study, undergraduate students viewed patient charts and entered numerical values from these charts into a medical record database. They were unexpectedly interrupted by secondary tasks that differed in relevance and complexity. The secondary tasks varied by whether they facilitated or inhibited (i.e., relevant or irrelevant) rehearsal of the suspended task and whether they placed a demand on working memory (i.e., high complexity or low complexity). The primary measures of interest were the duration of time needed to resume the primary task and perceived mental demand. The Memory for Goals model (Altmann & Trafton, 2002) predicts that task relevant interruptions would lead to faster task resumptions, when compared to task-irrelevant interruptions. The Time-Based Resource Sharing model (Barrouillet, 2007) predicts that high complexity interruptions would lead to slower task resumptions and higher perceived mental demand, when compared to moderate and low complexity interruptions. Alternatively, the Memory for Problem States model (Borst, 2015) predicts that high complexity and moderate complexity interruptions would not lead to significant differences in task resumption speed. Results revealed two important findings. First, participants resumed the primary task faster and reported lower perceived mental demand following relevant interruptions, when compared to irrelevant interruptions. Second, as the magnitude of interruption complexity increased, participants resumed the primary task slower and reported higher perceived mental demand. Thus, the findings offered support for the Memory for Goals and Time-Based Resource Sharing models, but not the Memory for Problem States model. In general, the current research illustrates the importance of minimizing the demand on attentional resources when interrupting individuals during the performance of visuospatial tasks, particularly when the interruption is irrelevant to the suspended primary task

PSBS: Practical Size-Based Scheduling

Size-based schedulers have very desirable performance properties: optimal or near-optimal response time can be coupled with strong fairness guarantees. Despite this, such systems are very rarely implemented in practical settings, because they require knowing a priori the amount of work needed to complete jobs: this assumption is very difficult to satisfy in concrete systems. It is definitely more likely to inform the system with an estimate of the job sizes, but existing studies point to somewhat pessimistic results if existing scheduler policies are used based on imprecise job size estimations. We take the goal of designing scheduling policies that are explicitly designed to deal with inexact job sizes: first, we show that existing size-based schedulers can have bad performance with inexact job size information when job sizes are heavily skewed; we show that this issue, and the pessimistic results shown in the literature, are due to problematic behavior when large jobs are underestimated. Once the problem is identified, it is possible to amend existing size-based schedulers to solve the issue. We generalize FSP -- a fair and efficient size-based scheduling policy -- in order to solve the problem highlighted above; in addition, our solution deals with different job weights (that can be assigned to a job independently from its size). We provide an efficient implementation of the resulting protocol, which we call Practical Size-Based Scheduler (PSBS). Through simulations evaluated on synthetic and real workloads, we show that PSBS has near-optimal performance in a large variety of cases with inaccurate size information, that it performs fairly and it handles correctly job weights. We believe that this work shows that PSBS is indeed pratical, and we maintain that it could inspire the design of schedulers in a wide array of real-world use cases.Comment: arXiv admin note: substantial text overlap with arXiv:1403.599

Evaluating the Probability of Channel Availability for Spectrum Sharing using Cognitive Radio

Spectrum sharing between service providers improves the spectral efficiency, probability efficiency of sensing and reduces the call blockage. If the number of service providers is increased to share the spectrum, this may reduce the high traffic patterns of the calls. In this paper, we present an approach for channel availability and call arrival rate. The results are used to evaluate the probability of the channel availability of a frequency band within a time period. In this work, we propose an algorithm for predicting the call arrival rate which used to predict the traffic process

Multi-agent control and operation of electric power distribution systems

This dissertation presents operation and control strategies for electric power distribution systems containing distributed generators. First, models of microturbines and fuel cells are developed. These dynamic models are incorporated in a power system analysis package. Second, operation of these generators in a distribution system is addressed and load following schemes are designed. The penetration of distributed generators (DGs) into the power distribution system stability becomes an issue and so the control of those DGs becomes necessary. A decentralized control structure based on conventional controllers is designed for distributed generators using a new developed optimization technique called Guided Particle Swarm Optimization. However, the limitations of the conventional controllers do not satisfy the stability requirement of a power distribution system that has a high DG penetration level, which imposes the necessity of developing a new control structure able to overcome the limitations imposed by the fixed structure conventional controllers and limit the penetration of DGs in the overall transient stability of the distribution system. Third, a novel multi-agent based control architecture is proposed for transient stability enhancement for distribution systems with microturbines. The proposed control architecture is hierarchical with one supervisory global control agent and a distributed number of local control agents in the lower layer. Specifically, a central control center supervises and optimizes the overall process, while each microturbine is equipped with its own local control agent.;The control of naval shipboard electric power system is another application of distributed control with multi-agent based structure. In this proposal, the focus is to introduce the concept of multi-agent based control architecture to improve the stability of the shipboard power system during faulty conditions. The effectiveness of the proposed methods is illustrated using a 37-bus IEEE benchmark system and an all-electric naval ship

Thermophilisation of communities differs between land plant lineages, land use types and elevation

Bryophytes provide key ecosystem services at the global scale such as carbon storage and primary production in resource limited habitats, but compared to vascular plants knowledge on how these organisms face recent climate warming is fragmentary. This is particularly critical because bryophytes differ fundamentally from vascular plants in their ecophysiological and biological characteristics, so that community alterations most likely have different dynamics. In a comparative approach, we analysed thermophilisation of bryophyte and vascular plant communities in 1146 permanent plots distributed along an elevational gradient of nearly 3.000 m in Switzerland (Central Europe) that were visited in 5-years intervals between 2001 and 2021. We estimated thermophilisation from changes in unweighted mean temperature indicator values of species, compared it to expected thermophilisation rates given the shift of isotherms and addressed differences between the two lineages, major land use types (managed grasslands, forests, unmanaged open areas), life strategy types (long- and short-lived species) and in elevation. Thermophilisation of bryophyte communities was on average 2.1 times higher than of vascular plant communities and at high elevations it approximated the expected rate given the shift of isotherms. Thermophilisation of both, bryophyte and vascular plant communities was not driven by a loss of cryophilic species but by an increase in thermophilic and mesophilic species, indicating an in-filling process. Furthermore, our data show that thermophilisation is higher in managed grasslands than in forests. We suggest that the higher responsiveness of bryophytes compared to vascular plants depends on their poikilohydry and dispersal capacity and that lower thermophilisation of forests communities is related to the buffering effect of microclimatic conditions in the interior of forests. Our study emphasises the heterogeneity of climate warming effects on plants because response dynamics differ between taxonomic groups as well as between land use types and along elevational gradients