This is the author's version of the work. It is posted here for your personal use. The definitive Version of Record was published in the 2023 7th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (ISMSI 2023), https://doi.org/10.1145/3596947.3596949. A System of Systems (SoS) comprises Constituent Systems (CSs) that interact to provide unique capabilities beyond any single CS. A key challenge in SoS is ad-hoc scalability, meaning the system size changes during operation by adding or removing CSs. This research focuses on an Unmanned Vehicle Fleet (UVF) as a practical SoS example, addressing uncertainties like mission changes, range extensions, and UV failures. The proposed solution involves a self-adaptive system that dynamically adjusts UVF architecture, allowing the Mission Control Center (MCC) to scale UVF size automatically based on performance criteria or manually by operator decision. A multi-agent environment and rule management engine were implemented to simulate and verify this approach. INTRODUCTION The System of Systems (SoS) terminology was created through multiple evolutionary steps [14].

Gartner predicts that by the end of 2024, 75% of enterprises will shift from piloting to operationalizing artificial intelligence (AI), and the vast majority of workloads will end up in the cloud in the long run. For some enterprises that plan to migrate to the cloud, the complexity, magnitude, and length of migrations may be daunting. The speed of different teams and their appetites for new tooling can vary dramatically. An enterprise's data science team may be hungry for adopting the latest cloud technology, while the application development team is focused on running their web applications on premises. Even with a multi-year cloud migration plan, some of the product releases must be built on the cloud in order to meet the enterprise's business outcomes.

An application architecture describes the patterns and techniques used to design and build an application. The architecture gives you a roadmap and best practices to follow when building an application so that you end up with a well-structured app. Application Architecture depicts different architecture aspects such as Functional Analysis, Implementation Architecture, Tools & Technology, Data, Non-Functional, Deployment Architecture, views of an Application. It enables you to envision the big picture and reduce cost by removing redundancies. Integrating components in the application and other systems are also clearly demarcated for everyone to visualize.

According to a top consulting report, if the Industry gets it right, linking the physical and digital worlds could generate up to $11.1 trillion a year in economic value by 2025. These have resulted in the exponential growth of the data generated through the IoT devices, which has created a requirement to bring computational power at individual device levels using edge computing rather than sending data to the cloud for analysis. Edge computing can move parts of the service-specific processing and data storage from the central cloud/datacenter to edge network nodes; when combined with Artificial Intelligence (AI), it can bring intelligence at the device level. This help to build a smart/intelligent connected network of edge devices called Edge AI or Edge AIoT (Artificial Intelligence of Things) or Intelligent Internet of Things. To know more about Edge AI please check out our blog on Edge AI: The Era of Distributed AI Computing.