GoalD: A Goal-Driven deployment framework for dynamic and heterogeneous computing environments

Abstract

Context: Emerging paradigms like Internet of Things and Smart Cities utilize advanced sensing and communication infrastructures, where heterogeneity is an inherited feature. Applications targeting such environments require adaptability and context-sensitivity to uncertain availability and failures in resources and their ad-hoc networks. Such heterogeneity is often hard to predict, making the deployment process a challenging task. Objective: This paper proposes GoalD as a goal-driven framework to support autonomous deployment of heterogeneous computational resources to fulfill requirements, seen as goals, and their correlated components on one hand, and the variability space of the hosting computing and sensing environment on the other hand. Method: GoalD comprises an offline and an online stage to fulfill autonomous deployment by leveraging the use of goals. Deployment configuration strategies arise from the variability structure of the Contextual Goal Model as an underlying structure to guide autonomous planning by selecting available as well as suitable resources at runtime. Results: We evaluate GoalD on an existing exemplar from the selfadaptive systems community -the Tele Assistance Service provided by Weyns and Calinescu [1]. Furthermore, we evaluate the scalability of GoalD on a repository consisting of 430,500 artifacts. The evaluation results demonstrate the usefulness and scalability of GoalD in planning the deployment of a system with thousands of components in a few milliseconds.Corresponding author -Postal Address: Dept. de Ciência da Computação -Campus Darcy Ribeiro, Edifício CIC/EST, Asa Norte, Brasília -DF -Brasil, Postal Code: 70910-900. Conclusions:GoalD is a framework to systematically tackle autonomous deployment in highly heterogeneous computing environments, partially unknown at design-time following a goal-oriented approach to achieve the user goals in a target environment. GoalD has demonstrated itself able to scale for deployment planning dealing with thousands of components in a few milliseconds.

Goal Controller Synthesis for Self-Adaptive Systems

“…Additionally, we aim to extend our EDGE notation and controller synthesis with support for runtime changes to the goal likelihood and the EDGE model structure (enabling their use for SAS whose goal variants evolve over time), and for "continuous" goals, i.e., goals that a SAS must achieve over a period of time (e.g., maintaining the throughput of a server or the navigation speed of a robot within given limits). Finally, we plan to evaluate EDGE thoroughly using multiple case studies drawn from the repository of software engineering for SAS exemplars at [30] and from our recent work on goaloriented approaches to SAS engineering [31]- [33].…”

BASBA: A framework for Building Adaptable Service-Based Applications

“…At the heart of many of such adaptation techniques, there is a component capable of designing, at runtime, a strategy for adapting to the changes in the environment, system, and requirements [38]. In addition, several goal-driven approaches are introduced to model the variability and guide the architectural design based on goal-oriented requirement engineering to provide a basis for the engineering of self-adaptive systems [39][40][41]. Goal-driven adaptation puts the emphasis on the requirements that need to be solved by the managing system for the concrete realization of self-adaptive systems [42].…”