Context-aware computing requires software that can adapt to changes in context. When contextual circumstances trigger multiple adaptations, software must also understand the relationships between these adaptations and react according to the rules governing these relationships. Adaptable software needs a means to establish and interpret these rules in order to avoid any undesirable and potentially catastrophic conflicts. This dissertation designs and implements the Adaptation Rules Management API (ArmAPI). ArmAPI has been demonstrated to work with a Context-Oriented Programming variation for Java called ContextJ* to execute conflict-free adaptations in two software applications. ArmAPI allows programmers to define relationship types between adaptations, and transfers these definitions to Prolog facts and rules. The Prolog engine, encapsulated within ArmAPI, then works with imperative algorithms to determine the appropriate adaptations to execute based on the current set of facts, rules, and contextual circumstances. Context represents all of the conditions for all of the entities known to an observing device. In any environment, context represents a large amount of data that can influence a multitude of conflicting adaptations. This research provides an incremental step towards overcoming the problem of adaptation conflict by constructing an API that considers the relationship types of inclusion, exclusion, ordering, conditional dependency, and independence. The API has been validated via two prototypes that provide typical scenarios.

The Intelligent Control Paradigm for software architecture is the result of this work. The Viable Software Approach is developed as an instance of the paradigm. The approach uses the Viable System Model as the basis for software system architecture. The result is a model-based architecture and approach for developing software systems by piecemeal adaptation with the goal that they become adaptive systems at runtime. Software built in this manner is called Viable Software. Viable Software represents a unifying class of self-controlling software that is an “intelligent” control system. Cybernetics, Control Theory, and Complexity Theory are the background for this work, and aspects relevant to this work are presented. These results are related to software architecture and software engineering. Rationale for the selection of the Viable System Model as a basis for software systems is given. The Viable System Model is described. The model is restated as an Alexanderian “pattern language” to make it more accessible to software engineering. A Viable Software Approach is proposed and expressed in the form of a Product Line Architecture that arranges the Viable System Model, the Viable Software Architecture, a Viable Component Framework, and a Component Transfer Protocol into a system for generative programming. An important result is the formalisation of the pattern of the Viable System into the interface specifications of the Viable Component. Three case studies illustrate the approach. The first is an analysis and extension of the Groove collaboration system. This study shows how the approach is used to map an existing system into the Viable Software Architecture and add fuzzy-adaptive user interface controllers. The second study presents the design and detailed software construction of an adaptive camera controller as part of a smart environment. The final study shows how a Business-to-Business e-Commerce system can be evolved and an expert system-based controller developed to implement business contracts.

The Intelligent Control Paradigm for software architecture is the result of this work. The Viable Software Approach is developed as an instance of the paradigm. The approach uses the Viable System Model as the basis for software system architecture. The result is a model-based architecture and approach for developing software systems by piecemeal adaptation with the goal that they become adaptive systems at runtime. Software built in this manner is called Viable Software. Viable Software represents a unifying class of self-controlling software that is an “intelligent” control system. Cybernetics, Control Theory, and Complexity Theory are the background for this work, and aspects relevant to this work are presented. These results are related to software architecture and software engineering. Rationale for the selection of the Viable System Model as a basis for software systems is given. The Viable System Model is described. The model is restated as an Alexanderian “pattern language” to make it more accessible to software engineering. A Viable Software Approach is proposed and expressed in the form of a Product Line Architecture that arranges the Viable System Model, the Viable Software Architecture, a Viable Component Framework, and a Component Transfer Protocol into a system for generative programming. An important result is the formalisation of the pattern of the Viable System into the interface specifications of the Viable Component. Three case studies illustrate the approach. The first is an analysis and extension of the Groove collaboration system. This study shows how the approach is used to map an existing system into the Viable Software Architecture and add fuzzy-adaptive user interface controllers. The second study presents the design and detailed software construction of an adaptive camera controller as part of a smart environment. The final study shows how a Business-to-Business e-Commerce system can be evolved and an expert system-based controller developed to implement business contracts.

The Intelligent Control Paradigm for software architecture is the result of this work. The Viable Software Approach is developed as an instance of the paradigm. The approach uses the Viable System Model as the basis for software system architecture. The result is a model-based architecture and approach for developing software systems by piecemeal adaptation with the goal that they become adaptive systems at runtime. Software built in this manner is called Viable Software. Viable Software represents a unifying class of self-controlling software that is an “intelligent” control system. Cybernetics, Control Theory, and Complexity Theory are the background for this work, and aspects relevant to this work are presented. These results are related to software architecture and software engineering. Rationale for the selection of the Viable System Model as a basis for software systems is given. The Viable System Model is described. The model is restated as an Alexanderian “pattern language” to make it more accessible to software engineering. A Viable Software Approach is proposed and expressed in the form of a Product Line Architecture that arranges the Viable System Model, the Viable Software Architecture, a Viable Component Framework, and a Component Transfer Protocol into a system for generative programming. An important result is the formalisation of the pattern of the Viable System into the interface specifications of the Viable Component. Three case studies illustrate the approach. The first is an analysis and extension of the Groove collaboration system. This study shows how the approach is used to map an existing system into the Viable Software Architecture and add fuzzy-adaptive user interface controllers. The second study presents the design and detailed software construction of an adaptive camera controller as part of a smart environment. The final study shows how a Business-to-Business e-Commerce system can be evolved and an expert system-based controller developed to implement business contracts.

The Intelligent Control Paradigm for software architecture is the result of this work. The Viable Software Approach is developed as an instance of the paradigm. The approach uses the Viable System Model as the basis for software system architecture. The result is a model-based architecture and approach for developing software systems by piecemeal adaptation with the goal that they become adaptive systems at runtime. Software built in this manner is called Viable Software. Viable Software represents a unifying class of self-controlling software that is an “intelligent” control system. Cybernetics, Control Theory, and Complexity Theory are the background for this work, and aspects relevant to this work are presented. These results are related to software architecture and software engineering. Rationale for the selection of the Viable System Model as a basis for software systems is given. The Viable System Model is described. The model is restated as an Alexanderian “pattern language” to make it more accessible to software engineering. A Viable Software Approach is proposed and expressed in the form of a Product Line Architecture that arranges the Viable System Model, the Viable Software Architecture, a Viable Component Framework, and a Component Transfer Protocol into a system for generative programming. An important result is the formalisation of the pattern of the Viable System into the interface specifications of the Viable Component. Three case studies illustrate the approach. The first is an analysis and extension of the Groove collaboration system. This study shows how the approach is used to map an existing system into the Viable Software Architecture and add fuzzy-adaptive user interface controllers. The second study presents the design and detailed software construction of an adaptive camera controller as part of a smart environment. The final study shows how a Business-to-Business e-Commerce system can be evolved and an expert system-based controller developed to implement business contracts.

The Intelligent Control Paradigm for software architecture is the result of this work. The Viable Software Approach is developed as an instance of the paradigm. The approach uses the Viable System Model as the basis for software system architecture. The result is a model-based architecture and approach for developing software systems by piecemeal adaptation with the goal that they become adaptive systems at runtime. Software built in this manner is called Viable Software. Viable Software represents a unifying class of self-controlling software that is an “intelligent” control system. Cybernetics, Control Theory, and Complexity Theory are the background for this work, and aspects relevant to this work are presented. These results are related to software architecture and software engineering. Rationale for the selection of the Viable System Model as a basis for software systems is given. The Viable System Model is described. The model is restated as an Alexanderian “pattern language” to make it more accessible to software engineering. A Viable Software Approach is proposed and expressed in the form of a Product Line Architecture that arranges the Viable System Model, the Viable Software Architecture, a Viable Component Framework, and a Component Transfer Protocol into a system for generative programming. An important result is the formalisation of the pattern of the Viable System into the interface specifications of the Viable Component. Three case studies illustrate the approach. The first is an analysis and extension of the Groove collaboration system. This study shows how the approach is used to map an existing system into the Viable Software Architecture and add fuzzy-adaptive user interface controllers. The second study presents the design and detailed software construction of an adaptive camera controller as part of a smart environment. The final study shows how a Business-to-Business e-Commerce system can be evolved and an expert system-based controller developed to implement business contracts.

The Intelligent Control Paradigm for software architecture is the result of this work. The Viable Software Approach is developed as an instance of the paradigm. The approach uses the Viable System Model as the basis for software system architecture. The result is a model-based architecture and approach for developing software systems by piecemeal adaptation with the goal that they become adaptive systems at runtime. Software built in this manner is called Viable Software. Viable Software represents a unifying class of self-controlling software that is an “intelligent” control system. Cybernetics, Control Theory, and Complexity Theory are the background for this work, and aspects relevant to this work are presented. These results are related to software architecture and software engineering. Rationale for the selection of the Viable System Model as a basis for software systems is given. The Viable System Model is described. The model is restated as an Alexanderian “pattern language” to make it more accessible to software engineering. A Viable Software Approach is proposed and expressed in the form of a Product Line Architecture that arranges the Viable System Model, the Viable Software Architecture, a Viable Component Framework, and a Component Transfer Protocol into a system for generative programming. An important result is the formalisation of the pattern of the Viable System into the interface specifications of the Viable Component. Three case studies illustrate the approach. The first is an analysis and extension of the Groove collaboration system. This study shows how the approach is used to map an existing system into the Viable Software Architecture and add fuzzy-adaptive user interface controllers. The second study presents the design and detailed software construction of an adaptive camera controller as part of a smart environment. The final study shows how a Business-to-Business e-Commerce system can be evolved and an expert system-based controller developed to implement business contracts.

The Intelligent Control Paradigm for software architecture is the result of this work. The Viable Software Approach is developed as an instance of the paradigm. The approach uses the Viable System Model as the basis for software system architecture. The result is a model-based architecture and approach for developing software systems by piecemeal adaptation with the goal that they become adaptive systems at runtime. Software built in this manner is called Viable Software. Viable Software represents a unifying class of self-controlling software that is an “intelligent” control system. Cybernetics, Control Theory, and Complexity Theory are the background for this work, and aspects relevant to this work are presented. These results are related to software architecture and software engineering. Rationale for the selection of the Viable System Model as a basis for software systems is given. The Viable System Model is described. The model is restated as an Alexanderian “pattern language” to make it more accessible to software engineering. A Viable Software Approach is proposed and expressed in the form of a Product Line Architecture that arranges the Viable System Model, the Viable Software Architecture, a Viable Component Framework, and a Component Transfer Protocol into a system for generative programming. An important result is the formalisation of the pattern of the Viable System into the interface specifications of the Viable Component. Three case studies illustrate the approach. The first is an analysis and extension of the Groove collaboration system. This study shows how the approach is used to map an existing system into the Viable Software Architecture and add fuzzy-adaptive user interface controllers. The second study presents the design and detailed software construction of an adaptive camera controller as part of a smart environment. The final study shows how a Business-to-Business e-Commerce system can be evolved and an expert system-based controller developed to implement business contracts.

With the explosion of the number of compute nodes, the bottleneck of future computing systems lies in the network architecture connecting the nodes. Addressing the bottleneck requires replacing current backplane-based network topologies. We propose to revolutionize computing electronics by realizing embedded optical waveguides for onboard networking and wireless chip-to-chip links at 200-GHz carrier frequency connecting neighboring boards in a rack. The control of novel rate-adaptive optical and mm-wave transceivers needs tight interlinking with the system software for runtime resource management.