Systems architecture

About: Systems architecture is a research topic. Over the lifetime, 17612 publications have been published within this topic receiving 283719 citations. The topic is also known as: system architecture.

Designing systems for adaptability by means of architecture options

Abstract: The value of a system usually diminishes over its lifetime, but some systems depreciate more slowly than others. Diminished value is due partly to the increasing needs and wants of the system's stakeholders and partly to its decreasing capabilities relative to emerging alternatives. Thus, systems are replaced or upgraded at substantial cost and disruption. If a system is designed to be changed and upgraded easily, however, this adaptability may increase its lifetime value. How can adaptability be designed into a system so that it will provide increased value over its lifetime? This paper describes the problem and an approach to its mitigation, adopting the concept of real options from the field of economics, extending it to the field of systems architecture, and coining the term architecture options for this next-generation method and the associated tools for design for adaptability. Architecture options provide a quantitative means of optimizing a system architecture to maximize its lifetime value. This paper provides two quantitative models to assess the value of architecture adaptability. First, we define three metrics—component adaptability factors, component option values, and interface cost factors—which are used in a static model to evaluate architecture adaptability during the design of new systems. Second, we enhance a dynamic model to evaluate architecture adaptability over the maintenance and upgrade lifetime of a system, formulating a Design for Dynamic Value (DDV) optimization model. We illustrate both models with quantitative examples and also discuss how to obtain the socio-economic data required for each model. © 2008 Wiley Periodicals, Inc. Syst Eng

IBM smart surveillance system (S3): a open and extensible framework for event based surveillance

Abstract: As smart surveillance technology becomes a critical component in security infrastructures, the system architecture assumes a critical importance. This paper considers the example of smart surveillance in an airport environment. We start with a threat model for airports and use this to derive the security requirements. These requirements are used to motivate an open-standards based architecture for surveillance. We discuss the critical aspects of this architecture and its implementation in the IBM S3 smart surveillance system. Demo results from a pilot deployment in Hawthorne, NY are presented.

Support for maintaining object-oriented programs

Abstract: It is explained how inheritance and dynamic binding make object-oriented programs difficult to maintain, and a concrete example of the problems that arise is given. It is shown that the difficulty lies in the fact that conventional tools are poorly suited for work with object-oriented languages, and it is argued that semantics-based tools are essential for effective maintenance of object-oriented programs. A system developed for working with C++ programs is described. It comprises a relational database system for information about programs and an interactive database interface integrated with a text editor. The authors describe the system architecture, detail the database relations, provide informal evidence on the system's effectiveness, and compare it to other research with similar goals. >

BodyCloud: Integration of Cloud Computing and body sensor networks

Abstract: Spatially distributed sensor nodes can be used to monitor systems and humans conditions in a wide range of application domains. A network of body sensors in a community of people generates large amounts of contextual data that requires a scalable approach for storage and processing. Cloud computing can provide a powerful, scalable storage and processing infrastructure to perform both online and offline analysis and mining of body sensor data streams. This paper presents BodyCloud, a system architecture based on Cloud Computing for the management and monitoring of body sensor data streams. It incorporates key concepts such as scalability and flexibility of resources, sensor heterogeneity, and the dynamic deployment and management of user and community applications.

Predicting software reliability with neural network ensembles

Abstract: Software reliability is an important factor for quantitatively characterizing software quality and estimating the duration of software testing period. Traditional parametric software reliability growth models (SRGMs) such as nonhomogeneous Poisson process (NHPP) models have been successfully utilized in practical software reliability engineering. However, no single such parametric model can obtain accurate prediction for all cases. In addition to the parametric models, non-parametric models like neural network have shown to be effective alternative techniques for software reliability prediction. In this paper, we propose a non-parametric software reliability prediction system based on neural network ensembles. The effects of system architecture on the performance are investigated. The comparative studies between the proposed system with the single neural network based system and three parametric NHPP models are carried out. The experimental results demonstrate that the system predictability can be significantly improved by combing multiple neural networks.