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.

GuideArch: guiding the exploration of architectural solution space under uncertainty

Abstract: A system's early architectural decisions impact its properties (e.g., scalability, dependability) as well as stakeholder concerns (e.g., cost, time to delivery). Choices made early on are both difficult and costly to change, and thus it is paramount that the engineer gets them "right". This leads to a paradox, as in early design, the engineer is often forced to make these decisions under uncertainty, i.e., not knowing the precise impact of those decisions on the various concerns. How could the engineer make the "right" choices in such circumstances? This is precisely the question we have tackled in this paper. We present GuideArch, a framework aimed at quantitative exploration of the architectural solution space under uncertainty. It provides techniques founded on fuzzy math that help the engineer with making informed decisions.

Taming subsystems: capabilities as universal resource access control in L4

Abstract: The embedded and mobile computing market with its wide range of innovations is expected to remain growing in the foreseeable future. Recent developments in the embedded computing technology offer more performance thereby facilitating applications of unprecedented utility. Open systems, such as Linux, provide access to a huge software base. Nevertheless, these systems have to coexist with critical device infrastructure that insists on stringent timing and security properties. In this paper, we will present a capability-based software architecture, featuring enforceable security policies. The architecture aims to support current and future requirements of embedded computing systems, such as running versatile third-party applications on general purpose and open operating systems side by side with security sensitive programs.

Agent-based Resource Management for Grid Computing

Abstract: It is envisaged that the grid infrastructure will be a large-scale distributed software system that will provide high-end computational and storage capabilities to differentiated users. A number of distributed computing technologies are being applied to grid development work, including CORBA and Jini. In this work, we introduce an A4 (Agile Architecture and Autonomous Agents) methodology, which can be used for resource management for grid computing. An initial system implementation utilises the performance prediction techniques of the PACE toolkit to provide quantitative data regarding the performance of complex applications running on local grid resources. At the meta-level, a hierarchy of identical agents is used to provide an abstraction of the system architecture. Each agent is able to cooperate with other agents to provide service advertisement and discovery to schedule applications that need to utilise grid resources. A performance monitor and advisor (PMA) is in development to optimize the performance of agent behaviours.

Synthesizing executable models of object oriented architectures

Abstract: The U.S. Department of Defense (DoD) has mandated the development of architectures to support the acquisition of systems that are interoperable and will meet the needs of military coalitions. This paper provides a general description of an architecting process based on object orientation and UML. It then provides a rationale for style constraints on the use of UML artifacts for representing DoD Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance (C4ISR) architectures. Finally the paper describes a mapping between the UML artifacts and an executable model based on colored Petri nets that can be used for logical, behavioral, and performance evaluation of the architecture. A procedure for the conversion is also provided. © 2003 Wiley Periodicals, Inc. Syst Eng 6: 266–300, 2003

A multi-agent architecture for cooperative inter-jurisdictional traffic congestion management

Abstract: This paper describes Cartesius , an innovative multi-agent architecture for the provision of real-time decision support to Traffic Operations Center personnel for coordinated, inter-jurisdictional traffic congestion management on freeway and surface street (arterial) networks. Cartesius is composed of two interacting knowledge-based systems that perform cooperative reasoning and resolve conflicts, for the analysis of non-recurring congestion and the on-line formulation of integrated control plans. The two agents support incident management operations for a freeway and an adjacent arterial subnetwork and interact with human operators, determining control recommendations in response to the occurrence of incidents. The multi-decision maker approach adopted by Cartesius reflects the spatial and administrative organization of traffic management agencies in US cities, providing a cooperative solution that exploits the agencies’ willingness to cooperate and unify their problem-solving capabilities, yet preserves the different levels of authority and the inherent distribution of data and expertise. The interaction between the agents is based on the functionally accurate, cooperative paradigm, a distributed problem solving approach aimed at producing consistent solutions without requiring the agents to have shared access to all globally available information. The cornerstone of this approach is the assumption that effective solutions can be efficiently obtained even when complete and up-to-date information is not directly available to the agents, thus reducing the need for complex data communication networks and synchronization time delays. The simulation-based evaluation of the system performance validates this assumption. The paper focuses on the distributed architecture of the agents and on their communication and decision making characteristics.