To adapt to volatile edge environments this paper envisages distributed systems built from small units of coordi-nation called microcompositions. Microcompositions decompose a single goal into subgoals and declaratively express compo-sition and coordination constraints. These microcompositions are managed by agents that self-organise themselves into a distributed management overlay structure - a Goal Realisation Tree (GRT) - based on goal realisation (means-ends) links. Both microcompositions and GRTs serve as runtime models, allowing agents to dynamically restructure them in response to changes in goals, service provision and context. Results from our evaluation demonstrate the effectiveness and scalability of our approach.

This paper envisages an agent-based approach for creating resilient, self-managing microservice systems. The approach is based on a categorisation of the adaptation space for microservices across two dimensions – application/infrastructure and service-type/composition. The monitoring and adaptation actions in the quadrants defined by these dimensions are distinct, requiring controllers/agents with different management capabilities. Based on this division of responsibility, an agent-oriented architectural approach is proposed – the Agent Mesh. A service mesh provides the observability and control of a network overlay that connects agents and services, while agents with the different capabilities defined above close the control loops at the application and infrastructure levels. A core feature of the approach is that both domain (managed) services and managing agents are integrated as microservices within the same mesh, and communicate with each other via sidecar proxies, thereby allowing adaptation of both the domain services and self-adaptation of the agents.

Resilience and antifragility are highly desirable properties for systems operating in dynamic, contested environments. Recent work has proposed an approach for achieving antifragility through three new self-* properties, one of which is adversarial self-exploration. In that approach, a single agent is responsible for defending a (distributed) managed system against an adversary. However, a major limitation is that the agent requires full observability of the managed system and its environment, which is not practical in many scenarios - including when a system operates in contested environments. We address this limitation by extending the approach to multi-agent self-exploration, where agents with partial observability and control of the managed system coordinate with other agents to compute the most resilient responses in the presence of adversaries. We demonstrate the feasibility and scalability of the proposed approach through extensive experimentation.

In this paper, we introduce a new meta-model that captures core concepts for constructing software architectures for general-purpose, autonomous middleware frameworks that realize internalized and externalized self-adaptivity at both a system- and meta-level in order to achieve antifragility. The proposed meta-model builds on, specializes, and complements existing multi-agent meta-models in line with a previously published reference model for antifragile systems in the cyber domain.

Resilience is an important property of distributed cyber defence systems operating in complex, adversarial environments. While resilience can be realized through self-management, implementing distributed self-management poses several significant challenges. In this paper, we identify some of these challenges and present our initial work on an approach for cyber resilience called AWaRE. The novelty of AWaRE lies in the use of a conceptual, state-space-based design and reconstitution framework, combined with run-time models and distributed constraint satisfaction/optimization techniques for decision-making and coordination of system re-configurations. The run-time models are generated via an expressive domain-specific language enabling component, constraint and agent modeling as well as constraint problem decomposition and architectural self-organization. We realize AWaRE via a concrete software framework, focusing specifically on autonomic self-* properties pertaining to distributed system configuration, deployment and reliable operation. We demonstrate the value of AWaRE in the context of a simple, cloud-based enterprise scenario.

Abstract Security methodologies represent systematic approaches for introducing security attributes into a system throughout the development lifecycle. While isolated attempts have been made to demonstrate the value of particular security methodologies, the “quality” of security methodologies, as such, has never been given due consideration; indeed, it has never been studied as a self‐standing topic. The literature therefore entirely lacks supportive artifacts that can provide a basis for assessing, and hence for improving, a security methodology's quality. In this paper, we fill the aforementioned gap by proposing a comprehensive quality framework and accompanying process, within the context of an existing approach to engineering security methodologies, which can be used for both (bottom‐up) quality assessment and (top‐down) quality improvement. The main framework elements can be extended and customized to allow an essentially arbitrary range of methodology features to be considered, thus forming a basis for flexible, fine‐grained quality control. We demonstrate the bottom‐up application of the latter framework and process on three real‐life security methodologies for distributed systems, taken as case studies. Based on the assessment results, we subsequently show in detail (for one) and briefly discuss (for the remaining set) how the case study methodologies can be re‐engineered to improve their quality.