The increasing number of IoT devices and digital services offers cross-domain sensing and control opportunities to a growing set of stakeholders. The provision of cross-domain digital services requires interoperability as a key enabler to bridge domain specifics, while inferring knowledge and allowing new data-driven services.

The complexity of IoT systems and tasks that are put before them require shifts in the way resources and service provisioning are managed. The concept of edge computing is introduced to enhance IoT systems' scalability, reactivity, efficiency, and privacy. In this paper, we present an edge computing solution for resource management of context-aware decision-making processes distributed between IoT gateways. The solution performs decision-making process management for smart actuation, based on analysis of sensory data streams, and context-informed edge computing resource and service provisioning management based on topology and operational changes. Our architectural solution showcases the first version of a Resource Management Framework - a generic framework for software resource orchestration best-suited to IoT platforms with event-driven, publish-subscribe communication mechanisms. Proof of concept experiments that are executed in a simulated edge computing testbed validate our solution's performance in improving the resilience and responsiveness of the edge computing system when there are operational and topology changes. Furthermore, the framework addresses the recovery of failed decision-making processes, impacting the overall health of the underlying IoT system.

The overarching connectivity of "things" in the Internet of Things presents an appealing environment for innovation and business ventures, but also brings a certain set of security challenges. Engineering secure Internet of Things systems requires addressing the peculiar circumstances under which they operate: constraints due to limited resources, high node churn, decentralized decision making, direct interfacing with end users etc. Thus, techniques and methodologies for building secure and robust Internet of Things systems should support these conditions. In this paper, we are presenting a description of the CAAVI-RICS framework, a novel security review methodology tightly coupled with distributed, Internet of Things and fog computing systems. With CAAVI-RICS we are exploring credibility, authentication, authorization, verification, and integrity (CAAVI) through explaining the rationale, influence, concerns and security solutions (RICS) that accompany them. Our contribution is a thorough systematic categorization and rationalization of security issues, covering the security landscape of Internet of Things/fog computing systems, as well as contributing to the discussion on the aspects of fog computing security and state-of-the-art solutions. Specifically, in this paper we explore the Authentication in Internet of Things systems through the RICS review methodology.