Generalized aggregate Quality of Service computation for composite services

This article addresses the problem of estimating the Quality of Service (QoS) of a composite service given the QoS of the services participating in the composition. Previous solutions to this problem impose restrictions on the topology of the orchestration models, limiting their applicability to well-structured orchestration models for example. This article lifts these restrictions by proposing a method for aggregate QoS computation that deals with more general types of unstructured orchestration models. The applicability and scalability of the proposed method are validated using a collection of models from industrial practice

Potential Economic Consequences of Local Nonconformity to Regional Land Use and Transportation Plans Using a Spatial Economic Model

To achieve the greenhouse gas (GHG) reduction targets that are required by California’s global warming legislation (AB32), the state of California has determined that recent growth trends in vehicle miles traveled (VMT) must be curtailed. In recognition of this, Senate Bill 375 (SB375) requires regional governments to develop land use and transportation plans or Sustainable Community Strategies (SCSs) that will achieve regional GHG targets largely though reduced VMT. Although the bill requires such a plan, it does not require local governments to adopt general plans that conform to this plan. In California, it is local, not regional, governments that have authority over land development decisions. Instead, SB375 relies on democratic participatory processes and relatively modest financial and regulatory incentives for SCS implementation. As a result, it is quite possible that some local governments within a region may decide not to conform to their SCS. In this study, a spatial economic model (PECAS) is applied in the Sacramento region (California, U.S.) to understand what the economic and equity consequences might be to jurisdictions that do and do not implement SCS land use plans in a region. An understanding of these consequences provides insight into jurisdictions’ motivations for compliance and thus, strategies for more effective implementation of SB375

Interference and Deployment Issues for Cognitive Radio Systems in Shadowing Environments

In this paper we describe a model for calculating the aggregate interference encountered by primary receivers in the presence of randomly placed cognitive radios (CRs). We show that incorporating the impact of distance attenuation and lognormal fading on each constituent interferer in the aggregate, leads to a composite interference that cannot be satisfactorily modeled by a lognormal. Using the interference statistics we determine a number of key parameters needed for the deployment of CRs. Examples of these are the exclusion zone radius, needed to protect the primary receiver under different types of fading environments and acceptable interference levels, and the numbers of CRs that can be deployed. We further show that if the CRs have apriori knowledge of the radio environment map (REM), then a much larger number of CRs can be deployed especially in a high density environment. Given REM information, we also look at the CR numbers achieved by two different types of techniques to process the scheduling information.Comment: to be presented at IEEE ICC 2009. This posting is the same as the original one. Only author's list is updated that was unfortunately not correctly mentioned in first versio

Software Reliability in Semantic Web Service Composition Applications

Web Service Composition allows the development of easily reconfigurable applications that can be quickly adapted to business changes. Due to the shift in paradigm from traditional systems, new approaches are needed in order to evaluate the reliability of web service composition applications. In this paper we present an approach based on intelligent agents for semiautomatic composition as well as methods for assessing reliability. Abstract web services, corresponding to a group of services that accomplishes a specific functionality are used as a mean of assuring better system reliability. The model can be extended with other Quality of Services – QoS attributes.Software Reliability, Web Service Composition, Intelligent Agents

Reducing bias and quantifying uncertainty in watershed flux estimates: the R package loadflex

Many ecological insights into the function of rivers and watersheds emerge from quantifying the flux of solutes or suspended materials in rivers. Numerous methods for flux estimation have been described, and each has its strengths and weaknesses. Currently, the largest practical challenges in flux estimation are to select among these methods and to implement or apply whichever method is chosen. To ease this process of method selection and application, we have written an R software package called loadflex that implements several of the most popular methods for flux estimation, including regressions, interpolations, and the special case of interpolation known as the period-weighted approach. Our package also implements a lesser-known and empirically promising approach called the “composite method,” to which we have added an algorithm for estimating prediction uncertainty. Here we describe the structure and key features of loadflex, with a special emphasis on the rationale and details of our composite method implementation. We then demonstrate the use of loadflex by fitting four different models to nitrate data from the Lamprey River in southeastern New Hampshire, where two large floods in 2006–2007 are hypothesized to have driven a long-term shift in nitrate concentrations and fluxes from the watershed. The models each give believable estimates, and yet they yield different answers for whether and how the floods altered nitrate loads. In general, the best modeling approach for each new dataset will depend on the specific site and solute of interest, and researchers need to make an informed choice among the many possible models. Our package addresses this need by making it simple to apply and compare multiple load estimation models, ultimately allowing researchers to estimate riverine concentrations and fluxes with greater ease and accuracy

Modeling Services Liberalization: The Case of Tanzania

This paper employs a 52-sector, small, open-economy computable general equilibrium model of the Tanzanian economy to assess the impact of the liberalization of regulatory barriers against foreign and domestic business service providers in Tanzania. The model incorporates productivity effects in both goods and services markets endogenously, through a Dixit-Stiglitz framework. It summarizes policy notes on the key business service sectors that were prepared for this work, and estimates the ad valorem equivalent of barriers to foreign direct investment based on these policy notes and detailed questionnaires completed by specialists in Tanzania. The authors estimate that Tanzania will gain about 5.3 percent of the value of Tanzanian consumption in the medium run (or about 4.8 percent of gross domestic product) from a full reform package that also includes uniform tariffs. The estimated gains increase to about 16 percent of consumption in the long-run, steady-state model, where the impact on the accumulation of capital from an improvement in the productivity of capital is taken into account. Decomposition exercises reveal that the largest gains to Tanzania will derive from liberalization of costly regulatory barriers that are non-discriminatory in their impacts between Tanzanian and multinational service providers.accounting; accurate estimate; aged; allocation; amount of money; baseline scenario; beneficiaries; beneficiary; Breast Cancer; budget constraint; calculation; central government; child care