Wireless Grids

2016 ◽  
pp. 293-320 ◽  
Author(s):  
Mariela J. Curiel H.
Keyword(s):  
Mobile Phones ◽  
Job Scheduling ◽  
Management Strategies ◽  
Simulation Models ◽  
Real Data ◽  
Battery Life ◽  
Wireless Devices ◽  
Grid Resource ◽  
Job Management ◽  
Wireless Grids

Wireless grids extend the capability of Grid Computing by including a collection of wireless devices of diverse characteristics, such as sensors, mobile phones, laptops and special instruments. These new resources increase the power and accessibility of grids. Wireless devices can be grid resource consumers or grid resource providers. This chapter focuses in the use of mobile devices as resource providers. Some characteristics of these resources, such as limited CPU power, small screen, short battery life, and intermittent disconnection, are genuine challenges for the development of job management strategies. Our goal is to depict recent proposals in resource discovering, monitoring and job scheduling. The main contributions of the last five years will be described along the chapter. The highlights of the review includes: the use of agent technology; solutions oriented to applications composed of independent tasks and the lack of studies using either real platforms or real data in simulation models.

Role of computer simulation in the application of knowledge to animal industries

1993 ◽  
Vol 44 (3) ◽  
pp. 541 ◽  
Author(s):  
JL Black ◽  
GT Davies ◽  
JF Fleming
Keyword(s):  
Management Strategies ◽  
Research Priorities ◽  
Simulation Models ◽  
Relative Price ◽  
Biological Efficiency ◽  
Future Research ◽  
Mechanistic Models ◽  
Animal Performance ◽  
Financial Return ◽  
Widespread Application

The net financial return of an enterprise depends on the interaction among a great many factors. Some of these factors relate to the animal, some to its diet, some to its environment, some to the prevalence of disease and some to circumstances outside the production enterprise such as the premiums paid for products of different quality, the relative price structure of feeds and products, and the availability and cost of capital, labour, breeding stock and other resources. Although there has been a great deal of research into many of these factors, the complexity of the interactions between them makes it virtually impossible for the human mind to assess accurately the consequences of alternative management strategies on either the efficiency of production or the long-term profitability of a livestock enterprise. By transforming the concepts and knowledge into mathematical equations and integrating them in computer programs using simulation modelling techniques, this vast store of information can be applied directly to improving the management of commercial animal enterprises. Models are also valuable for defining research priorities. These simulation models should, as far as possible, be based on descriptions of the mechanisms perceived to determine animal function, not on empirical relationships of correlation and association. This need for mechanistic models has major implications for the direction and nature of future research into animal function. Mechanistic models of animal performance alone are unlikely to result in the widespread application of knowledge to the animal industries. Models must be integrated with other modules that cover the major areas of an enterprise determining its profitability, as well as with programming features that make the whole Decision Support Software System easy to use and interpret by industry personnel. The animal model is likely to represent less than 20% of a commercially useful package. A major factor limiting the application of animal growth models is lack of an adequate description of the conditions within commercial enterprises. Collection of such data is difficult and frequently regarded as unattractive by scientists and funding organisations, but it is essential for effective application of existing knowledge through simulation models. Furthermore, industry must make frequent measurements of factors determining animal performance and enterprise profitability if the significance of predictions from animal models is to be evaluated fully. An example is presented illustrating how simulation models can improve the biological efficiency and profitability of a commercial animal enterprise when this information is available.

Developing Brand Assets with Wireless Devices

2005 ◽  
pp. 175-192 ◽  
Author(s):  
Jari H. Helenius ◽  
Veronica Liljander
Keyword(s):  
Literature Review ◽  
Mobile Phones ◽  
Communication Channels ◽  
Wireless Devices ◽  
Mobile Telecommunications ◽  
Mobile Channel ◽  
Managerial Implications

Advancements of the wired Internet and mobile telecommunications offer companies new opportunities for branding but also create a need to develop the literature to incorporate the new communication channels. This chapter focuses on the mobile channel and how mobile phones can be used in branding activities. Based on a literature review and practical examples, the chapter discusses how brand managers can utilize the mobile channel to strengthen brand assets. Four mobile branding (m-branding) techniques are proposed and their impact on brand assets discussed. Managerial implications and suggestions for further research are provided.

Electronic Business over Wireless Device

2011 ◽  
pp. 384-396
Author(s):  
Richi Nayak ◽  
Anurag Nayak
Keyword(s):  
Mobile Phones ◽  
Exponential Growth ◽  
Electronic Business ◽  
Wireless Devices ◽  
Business Applications ◽  
Wireless Device ◽  
Basic Concepts ◽  
High Level ◽  
The Voice

Research and practices in electronic businesses over wireless devices have recently seen an exponential growth. This chapter presents the basic concepts necessary to understand m-business applications and a case study of the voice driven airline-ticketing system that can be accessed at any time, anywhere by mobile phones. This application offers maximum functionality while still maintaining a high level of user convenience in terms of input and navigation.

Self-Configuration and Administration of Wireless Grids

2011 ◽  
pp. 255-268
Author(s):  
Ashish Agarwal ◽  
Amar Gupta
Keyword(s):  
Quality Of Service ◽  
Wireless Devices ◽  
Self Administration ◽  
Limited Bandwidth ◽  
Wireless Grids ◽  
Grid Topology ◽  
Adequate Quality ◽  
Limited Power ◽  
Wireless Grid

A Wireless Grid is an augmentation of a wired grid that facilitates the exchange of information and the interaction between heterogeneous wireless devices. While similar to the wired grid in terms of its distributed nature, the requirement for standards and protocols, and the need for adequate Quality of Service; a Wireless Grid has to deal with the added complexities of the limited power of the mobile devices, the limited bandwidth, and the increased dynamic nature of the interactions involved. This complexity becomes important in designing the services for mobile computing. A grid topology and naming service is proposed which can allow self-configuration and self-administration of various possible wireless grid layouts.

Dynamical Simulation Models of the Open Source Development Process

2008 ◽  
pp. 698-721
Author(s):  
I. P. Antoniades ◽  
I. Samoladas ◽  
I. Stamelos ◽  
L. Angelis
Keyword(s):  
Open Source ◽  
General Framework ◽  
Development Process ◽  
Simulation Models ◽  
Real Data ◽  
Simulation Methods ◽  
Dynamical Simulation ◽  
Closed Source ◽  
Free Open Source ◽  
Open Source Development

This chapter will discuss attempts to produce formal mathematical models for dynamical simulation of the development process of Free/Open Source Software (F/OSS) projects. First, a brief overview for simulation methods of closed source software development is given. Then, based on empirical facts reported in F/OSS case studies, we describe a general framework for F/OSS dynamical simulation models and discuss its similarities and differences to closed source software simulation. A specific F/OSS simulation model is introduced. The model is applied to the Apache project and to the gtk+ module of the GNOME project, and simulation outputs are compared to real data. The potential of formal F/OSS simulation models to turn into practical tools used by F/OSS coordinators to predict key project factors is demonstrated. Finally, issues for further research and efforts for improvement of this first-attempt model are discussed.

M-Learning with Mobile Phones

2009 ◽  
pp. 1344-1350
Author(s):  
Simon So
Keyword(s):  
Mobile Phones ◽  
Rapid Evolution ◽  
Developed Countries ◽  
Wireless Devices ◽  
Mobile Wireless ◽  
Web Based ◽  
Wireless Technologies ◽  
Internet Users ◽  
E Learning ◽  
Future Direction

The Internet is a major driver of e-learning advancement and there was an estimate of over 1000 million Internet users in 2004. The ownership of mobile devices is even more astonishing. ITU (2006) reported that 77% of the population in developed countries are mobile subscribers. The emergence of mobile, wireless and satellite technologies is impacting our daily life and our learning. New Internet technologies are being used to support small-screen mobile and wireless devices. In a field marked by such rapid evolution, we cannot assume that the Web as we know it today will remain the primary conduit for Internet- based learning (Bowles, 2004, p.12). Mobile and wireless technologies will play a pivotal role in learning. This new field is commonly known as mobile learning (m-learning). In this article, the context of m-learning in relation to e-learning and d-learning is presented. Because of the great importance in Web-based technologies to bridge over mobile and wireless technologies, the infrastructure to support mlearning through browser-based technologies is described. This concept represents my own view on the future direction of m-learning. An m-learning experiment, which implemented the concept, is then presented.

scholarly journals Brief history and future of animal simulation models for science and application

2014 ◽  
Vol 54 (12) ◽  
pp. 1883 ◽  
Author(s):  
J. L. Black
Keyword(s):  
Animal Models ◽  
Real Time ◽  
Dynamic Models ◽  
Management Strategies ◽  
Simulation Models ◽  
Real Time Control ◽  
Livestock Farming ◽  
Animal Metabolism ◽  
The Impact ◽  
Further Development

Mathematical equations have been used to add quantitative rigour to the description of animal systems for the last 100 years. Initially, simple equations were used to describe the growth of animals or their parts and to predict nutrient requirements for different livestock species. The advent of computers led to development of complex multi-equation, dynamic models of animal metabolism and of the interaction between animals and their environment. An understanding was developed about how animal systems could be integrated in models to obtain the most realistic prediction of observations and allow accurate predictions of as yet unobserved events. Animal models have been used to illustrate how well animal systems are understood and to identify areas requiring further research. Many animal models have been developed with the aim of evaluating alternative management strategies within animal enterprises. Several important gaps in current animal models requiring further development are identified: including a more mechanistic representation of the control of feed intake; inclusion of methyl-donor requirements and simulation of the methionine cycle; plus a more mechanistic representation of disease and the impact of microbial loads under production environments. Reasons are identified why few animal models have been used for day-to-day decision making on farm. In the future, animal simulation models are envisaged to function as real-time control of systems within animal enterprises to optimise animal productivity, carcass quality, health, welfare and to maximise profit. Further development will be required for the integration of models that run real time in enterprise management systems adopting precision livestock farming technologies.

Systemic modelling of soil functions under the impact of agricultural management

2020 ◽  
Author(s):  
Sara König ◽  
Ulrich Weller ◽  
Birgit Lang ◽  
Mareike Ließ ◽  
Stefanie Mayer ◽  
...  
Keyword(s):  
Soil Structure ◽  
Water Distribution ◽  
Management Strategies ◽  
Simulation Models ◽  
Crop Growth ◽  
Soil Productivity ◽  
Soil Functions ◽  
Management Options ◽  
Soil Organic Matter Turnover ◽  
The Impact

<p>The increasing demand for food and bio-energy gives need to optimize soil productivity, while securing other soil functions such as nutrient cycling and buffer capacity, carbon storage, biological activity, and water filter and storage. Mechanistic simulation models are an essential tool to fully understand and predict the complex interactions between physical, biological and chemical processes of soil with those functions, as well as the feedbacks between these functions.</p><p>We developed a systemic soil model to simulate the impact of different management options and changing climate on the named soil functions by integrating them within a simplified system. The model operates on a 1d soil profile consisting of dynamic nodes, which may represent the different soil horizons, and integrates different processes including dynamic water distribution, soil organic matter turnover, crop growth, nitrogen cycling, and root growth.</p><p>We present the main features of our model by simulating crop growth under various climatic scenarios on different soil types including management strategies affecting the soil structure. We show the relevance of soil structure for the main soil functions and discuss different model outcome variables as possible measures for these functions.</p><p>Further, we discuss ongoing model extensions, especially regarding the integration of biological processes, and possible applications.</p>

A criteria-set for the construction of a model cascade for fall-to-flow landslide chains

2020 ◽  
Author(s):  
Nina Marlovits ◽  
Martin Mergili ◽  
Alexander Preh ◽  
Thomas Glade
Keyword(s):  
Risk Management ◽  
Process Model ◽  
Management Strategies ◽  
Simulation Models ◽  
Spatial Transformation ◽  
Negative Consequences ◽  
Cascading Effects ◽  
Flow Models ◽  
Flow Processes ◽  
Risk Management Strategies

<p>Some of the most destructive landslide events in history have evolved through cascading effects where, for example, a rock fall in High Alpine areas transforms into a flow of rock, debris, ice, or snow. Amplification effects often result in high velocities and energies. As a result, such events can destroy private properties, infrastructure or can even lead to loss of life even in areas distant from the source.</p><p>In order to reduce the negative consequences of cascading landslide processes, numerical modelling can enrich the efficiency of risk management strategies. Unfortunately, most landslide run-out simulation models are designed either for fall or flow processes. However, it is presumed that, at least in some cases, cascading effects cannot be properly represented by only one single process model. Due to the complexity of combining and comparing models for fall and flow processes, not many attempts to do so have been documented.</p><p>In an attempt to fill this gap, the primary goal of this study is to define a criteria-set on how and when to couple the models, based on appropriate key parameters. Hence, we analyse computer models for fall and flow processes and evaluate whether their combination can provide an appropriate description of cascading landslides. A set of well-documented fall-flow events is back-calculated. Fall and flow are first simulated separately, with some overlap, each with a tool tailored for the corresponding process, based on detailed information on the case study. The input and output parameters for the overlapping areas are then analysed to investigate how and when process chains are linked. Thereby, one of the key challenges consists in the spatial transformation of the output of fall models to the input of flow models.</p><p>The findings will be used to develop a simulation framework allowing for the automated combination of fall and flow models In order to efficiently perform simulations which can be used as input for the design of hazard and risk management measures.</p>

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