Background: Self-awareness has been recently receiving a ention in computing systems for enriching autonomous so ware systems operating in dynamic environments. Objective: We aim to investigate the adoption of computational self-awareness concepts in autonomic so ware systems, and motivate future research directions on self-awareness and related problems. Method: We conducted a systemic literature review to compile the studies related to the adoption of self-awareness in so ware engineering and explore how self-awareness is engineered and incorporated in so ware systems. From 865 studies, 74 studies have been selected as primary studies. We have analysed the studies from multiple perspectives, such as motivation, inspiration, and engineering approaches, among others. Results: Results have shown that self-awareness has been used to enable self-adaptation in systems that exhibit uncertain and dynamic behaviour. ough the recent a empts to de ne and engineer self-awareness in so ware engineering, there is no consensus on the de nition of self-awareness. Also, the distinction between self-aware and self-adaptive systems has not been systematically treated. Conclusions: Our survey reveals that self-awareness for so ware systems is still a formative eld and that there is growing a ention to incorporate self-awareness for be er reasoning about the adaptation decision in autonomic systems. Many pending issues and open problems, outlining possible research directions. CCS Concepts: •General and reference → Surveys and overviews; General literature; •Social and professional topics → So ware selection and adaptation; •So ware and its engineering → So ware con guration management and version control systems;

Background —The proliferation of cloud services has opened a space for cloud brokerage services. Brokers intermediate between cloud customers and providers to assist the customer in selecting the most suitable service, helping to manage the dimensionality, heterogeneity, and uncertainty associated with cloud services. Objective —Unlike other surveys, this survey focuses on the customer perspective. The survey systematically analyses the literature to identify and classify approaches to realise cloud brokerage, presenting an understanding of the state-of-the-art and a novel taxonomy to characterise cloud brokers. Method —A systematic literature survey was conducted to compile studies related to cloud brokerage and explore how cloud brokers are engineered. These studies are then analysed from multiple perspectives, such as motivation, functionality, engineering approach, and evaluation methodology. Results —The survey resulted in a knowledge base of current proposals for realising cloud brokers. The survey identified differences between the studies’ implementations, with engineering efforts directed at combinations of market-based solutions, middlewares, toolkits, algorithms, semantic frameworks, and conceptual frameworks. Conclusion —Our comprehensive meta-analysis shows that cloud brokerage is still a formative field. Although significant progress has been achieved in this field, considerable challenges remain to be addressed, which are also identified in this survey.

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As the number of connected devices rapidly increases, largely thanks to uptake of IoT technologies, there is significant stimulus to enable opportunistic interactions between different systems that encounter each other at run time. However, this is complicated by diversity in IoT technologies and implementation details that are not known in advance. To achieve such unplanned interactions, we use the concept of a holon to represent a system's services and requirements at a high level. A holon is a self-describing system that appears as a whole when viewed from above whilst potentially comprising multiple subsystems when viewed from below. In order to realise this world view and facilitate opportunistic system interactions, we propose the idea of using ontologies to define and program a holon. Ontologies offer the ability to classify the concepts of a domain, and use this formalised knowledge to infer new knowledge through reasoning. In this paper, we design a holon ontology and associated code generation tools. We also explore a case study of how programming holons using this approach can aid an IoT system to self-describe and reason about other systems it encounters. As such, developers can develop system composition logic at a high-level without any preconceived notions about low-level implementation details.

Abstract-Volunteered Service Composition (VSC) refers to the process of composing volunteered services and resources. These services are typically published to a pool of voluntary resources. Selection and composition decisions tend to encounter numerous uncertainties: service consumers and applications have little control of these services and tend to be uncertain about their level of support for the desired functionalities and nonfunctionalities. In this paper, we contribute to a self-awareness framework that implements two levels of awareness, Stimulusawareness and Time-awareness. The former responds to basic changes in the environment while the latter takes into consideration the historical performance of the services. We have used volunteer service computing as an example to demonstrate the benefits that self-awareness can introduce to self-adaptation. We have compared the Stimulus-and Time-awareness approaches with a recent Ranking approach from the literature. The results show that the Time-awareness level has the advantage of satisfying higher number of requests with lower time cost.