Edge computing brings cloud services closer to the edge of the network, where data originates, and dramatically reduces the network latency of the cloud. It is a bridge linking clouds and users making the foundation for novel interconnected applications. However, edge computing still faces many challenges like remote configuration, well-defined native applications model, and limited node capacity. It lacks geo-organization and a clear separation of concerns. As such edge computing is hard to be offered as a service for future real-time user-centric applications. This paper presents the dynamic organization of geo-distributed edge nodes into micro data-centers to cover any arbitrary area and expand capacity, availability, and reliability. A cloud organization is used as an influence with adaptations for a different environment, and a model for edge applications utilizing these adaptations is presented. It is argued that the presented model can be integrated into existing solutions or used as a base for the development of future systems. Furthermore, a clear separation of concerns is given for the proposed model. With the separation of concerns setup, edge-native applications model, and a unified node organization, we are moving towards the idea of edge computing as a service, like any other utility in cloud computing.

The micro cloud model offers cloud behavior at the edge of the network. It allows dynamic organization of the resources, closer to the users and the data. One of the crucial problems to solve is to design a proper cloud model at the edge of the network and offer cloud services that support multi-tenancy. This cloud property is a governing mechanism to lower cloud costs. It is essential for the scalability of both public and private clouds due to the utilization of shared resources and the logical separation of tenants. This paper presents the model for the creation of virtual clouds (vClouds) on physical infrastructure using a hierarchy of namespaces, with proper organization and redistribution of resources such as CPU, RAM, and storage, while preserving logical isolation between vClouds, thus creating a multi-tenant system. The presented model guarantees accurate resource redistribution through graph transformations to model operations, while the proposed protocols ensure correctness by employing multiparty session types for modeling. We extend the secure computing mode to establish an isolated system, allowing sandboxing rules for every namespace and creating hierarchies of security profiles. This advancement enables our model to inherit parent security profiles fully, extend them by adding child-specific elements, or redefine and create entirely new ones. Furthermore, the users can switch context, meaning they can change vCloud or the namespace they operate on.

Edge computing offers cloud services closer to data sources and end-users, making the foundation for novel applications. The infrastructure deployment is taking off, bringing new challenges: how to use geo-distribution properly, or harness the advantages of having resources at a specific location? New real-time applications require multi-tier infrastructure, preferably doing data preprocessing locally, but using the cloud for heavy workloads. We present a model, able to organize geo-distributed nodes into micro clouds dynamically, allowing resource reorganization to best serve population needs. Such elasticity is achieved by relying on cloud organization principles, adapted for a different environment. The desired state is specified descriptively, and the system handles the rest. As such, infrastructure is abstracted to the software level, thus enabling “infrastructure as software” at the edge. We argue about blending the proposed model into existing tools, allowing cloud providers to offer future micro clouds as a service.

In modern architecture, multi-tenancy is the design mode of operation used to reduce the resource costs of system implementation. This architectural decision does not come without additional costs when managing isolation and data privacy between the tenants. That is a known challenge in cloud computing that translates to systems closer to the users, namely edge computing and micro clouds. Existing data management solutions, while supporting multi-tenancy, need help to handle the dynamic nature of such environments, limiting their ability to scale and support collaborative applications across different clusters or regions. This paper addresses the limitations of current data management solutions in supporting dynamic organization, configuration, and collaboration in multi-tenant, geo-distributed micro clouds at the edge. By extending the existing virtual clouds model, we introduce a new dataspaces layer and protocols for data discovery using the concept of hierarchical namespaces and transforming non-shareable resources, such as files and folders, into collaborative resources. We propose two types of collaborative applications, leveraging stored procedures and event triggers for data consumption. Finally, we ensure that the model provides accurate access and redistribution of shareable (CPU, RAM, disk) and non-shareable resources through graph transformation theory, with correctness validated using multiparty session types. That enables more flexible programming for collaborative applications, improving connectivity across distributed storage systems and allowing resource borrowing between applications within the same organization. This research seeks to bridge the gap between current tools and the demands of modern distributed systems, enabling more robust, adaptable, and collaborative data management solutions.