As the Unified Modeling Language (UML) and modeldriven development (MDD) become increasingly common in industry, many developers are faced with the difficult task of understanding how an existing UML model realizes sy...
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As the Unified Modeling Language (UML) and modeldriven development (MDD) become increasingly common in industry, many developers are faced with the difficult task of understanding how an existing UML model realizes system requirements. Essentially, developers are required to understand the structure and behavior of UML models that they may have not created. Understanding these relationships is non-trivial, because the interactions in the model are not readily apparent. Commonly, the only means to elicit these relationships is visual inspection and guided simulation. This paper describes an alternative approach termed REVU (Requirements Visualization of UML), a process for visualizing functional requirements in terms of behavioral interactions in a UML model. We illustrate the use of this process with the visualization of scenarios for an adaptive light control system.
In previous years, many studies have been conducted on grid computing, in which users and resource providers organize various virtual organizations (VOs) to share resources and services. A VO organizes other sub-VOs f...
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In previous years, many studies have been conducted on grid computing, in which users and resource providers organize various virtual organizations (VOs) to share resources and services. A VO organizes other sub-VOs for the purpose of achieving the VO goal, which forms the hierarchical VO environment. In this paper, we model and formalize the resource allocation problem in hierarchical VOs. Resource providers and VOs agree upon the VO resource sharing policy, such as resource sharing amount and resource usage cost for VOs. We provide the resource allocation scheme of a VO resource broker to minimize the total cost in order to meet a user's job deadline. In addition, we deal with several cost adjustment methods in resource providers to utilize their resources efficiently in hierarchical VOs
Grid computing has emerged as an effective means of facilitating the sharing of distributed heterogeneous resources, enabling collaboration in large scale environments. However, the nature of grid systems coupled with...
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Grid computing has emerged as an effective means of facilitating the sharing of distributed heterogeneous resources, enabling collaboration in large scale environments. However, the nature of grid systems coupled with the overabundance and fragmentation of information, makes it difficult to monitor resources, services, and computations in order to plan and make decisions. In this paper we present Gridscape II, a customisable portal component that can be used on its own or plugged-in to compliment existing grid portals. Gridscape II manages the gathering of information from arbitrary, heterogeneous and distributed sources and presents them together seamlessly within a single interface. It also leverages the Google Maps API in order to provide a highly interactive user interface. Gridscape II is simple and easy to use, providing a solution to those users who do not wish to invest heavily in developing their own monitoring portal from scratch, and also for those users who want something easy to customise and extend for their specific needs
The advent of service-oriented grid computing has resulted in the need for grid resources such as clusters to enforce user-specific service needs and expectations. Service level agreements (SLAs) define conditions whi...
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The advent of service-oriented grid computing has resulted in the need for grid resources such as clusters to enforce user-specific service needs and expectations. Service level agreements (SLAs) define conditions which a cluster needs to fulfill for various jobs. An example of SLA requirement is the deadline by which a job has to be completed. In addition, these clusters implement job admission control so that overall service performance does not deteriorate due to accepting exceeding amount of jobs. However, their effectiveness is highly dependent on accurate runtime estimates of jobs. This paper thus examines the adverse impact of inaccurate runtime estimates for deadline constrained job admission control in clusters using the earliest deadline first (EDF) strategy and a deadline-based proportional processor share strategy called Libra. Simulation results show that an enhancement called LibraRisk can manage the risk of inaccurate runtime estimates better than EDF and Libra by considering the risk of deadline delay
FlowUML is a logic-based system to validate information flow policies at the requirements specification phase of UML based designs. It uses Horn clauses to specify information flow polices that can be checked against ...
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An algorithm for time division multiple access (TDMA) is found to be applicable in converting existing distributed algorithms into a model that is consistent with sensor networks. Such a TDMA service needs to be self-...
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Over the last few years, grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models. Users consume these services based on th...
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Over the last few years, grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models. Users consume these services based on their QoS (quality of service) requirements. In such “pay-per-use” grids, workflow execution cost must be considered during scheduling based on users' QoS constraints. In this paper, we propose a budget constraint based scheduling, which minimizes execution time while meeting a specified budget for delivering results. A new type of genetic algorithm is developed to solve the scheduling optimization problem and we test the scheduling algorithm in a simulated grid testbed.
Evacuation planning plays a significant role in building evacuation. The purpose of this paper is to demonstrate how an evolutionary computation technique in the form of an estimation of distribution algorithm can be ...
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Evacuation planning plays a significant role in building evacuation. The purpose of this paper is to demonstrate how an evolutionary computation technique in the form of an estimation of distribution algorithm can be used in evacuation planning. This technique is used to evolve the number and location of exits in order to minimize overall evacuation time and reduce the number of casualties and injuries. The algorithm is applied to three day-care layouts, classified as playroom, lunchroom, and classroom settings. The algorithm generates an optimal or near-optimal configuration, and results across several trials can be used to determine the probability that an exit is needed for each possible location. The best exit configurations are presented for each of the three layouts, and a brief analysis is discussed. Although evacuation planning presented in this paper is focused on room layouts, evolutionary computation techniques have the potential to be implemented in large-scale evacuation planning
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