22,238 research outputs found

    An Analysis of Service Trading Architectures

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    Automating the creation and management of SLAs in elec tronic commerce scenarios brings many advantages, such as increasing the speed in the contracting process or allowing providers to deploy an automated provision of services based on those SLAs. We focus on the service trading process, which is the process of locating, selecting, nego tiating, and creating SLAs. This process can be applied to a variety of scenarios and, hence, their requirements are also very different. Despite some service trading architectures have been proposed, currently there is no analysis about which one fits better in each scenario. In this paper, we define a set of properties for abstract service trading architectures based on an analysis of several practical scenarios. Then, we use it to analyse and compare the most relevant abstract architectures for service trad ing. In so doing, the main contribution of this article is a first approach to settle the basis for a qualitative selection of the best architecture for similar trading scenarios

    Characterization and Modeling of Spectrum Trading Markets

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    Telecommunication regulators are facing increasing pressure to make spectrum resources more widely available to new wireless services and providers. In spectrum trading markets, buyers and sellers determine the assignments of spectrum and, possibly, its uses. These markets are being considered or implemented by the regulatory bodies of many countries as a way to provide increasing efficiency in the use of spectrum and attend the demand for this resource. This work describes a classification for the implementation of spectrum trading markets and a way to model them and identify the conditions for their viability. Specifically, we make use of Agent-Based Computational Economics (ACE) to model the participants in these markets, analyze the behaviors that emerge from the interactions of its participants and determine the conditions for viable markets. Our results, provide guidelines that can be used by regulators and wireless service providers for the design and implementation of these markets

    The viability of spectrum trading markets

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    Spectrum trading markets are of growing interest to many spectrum management agencies. They are motivated by their desire to increase the use of market based mechanisms for spectrum management and reduce their emphasis on command and control methods. Despite the liberalization of regulations on spectrum trading in some countries, spectrum markets have not yet emerged as a key spectrum assignment component. The lack of liquidity in these markets is sometimes cited as a primary factor in this outcome. This work focuses on determining the conditions for viability of spectrum trading markets by considering scenarios with different market structures, number of trading participants and amount of tradable spectrum. We make use of Agent-Based Computational Economics (ACE) to analyze each market scenario and the behaviors of its participants. Our models indicate that spectrum markets can be viable in a service if sufficient numbers of market participants exist and the amount of tradable spectrum is balanced to the demand. We use the results of this analysis and the characteristics of the viable markets found to make recommendations for the design of spectrum trading markets. Further work will explore more complicated scenarios. ©2010 IEEE

    Automated ANN alerts : one step ahead with mobile support

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    In this paper, I examine the potential of mobile alerting services empowering investors to react quickly to critical market events. Therefore, an analysis of short-term (intraday) price effects is performed. I find abnormal returns to company announcements which are completed within a timeframe of minutes. To make use of these findings, these price effects are predicted using pre-defined external metrics and different estimation methodologies. Compared to previous research, the results provide support that artificial neural networks and multiple linear regression are good estimation models for forecasting price effects also on an intraday basis. As most of the price effect magnitude and effect delay can be estimated correctly, it is demonstrated how a suitable mobile alerting service combining a low level of user-intrusiveness and timely information supply can be designed
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